Papers - MUKUNOKI Masayuki
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Takatsuka Kayoko, Nagatomo Yoki, Uchida Noriyuki, Ikeda Takuya, Mukunoki Masayuki, Okazaki Naonobu
Journal of Robotics, Networking and Artificial Life 10 ( 1 ) 17 - 24 2023.6
Language：English Publishing type：Research paper (scientific journal) Publisher：ALife Robotics Corporation Ltd.
This study aimed to reduce the effect of the examining environment on accuracy by using an eye movement detection system, a VR head-mounted display. We reproduced the inspection environment in a virtual reality environment and performed the cover test, a basic inspection technique for tropia and phoria. We then developed a system that uses eye data collected by eye tracking to detect the directions and magnitudes of eye misalignment. The Maddox method, an existing testing procedure, was used to verify the accuracy. We have confirmed its effectiveness in detecting the directions and magnitudes of horizontal eye misalignment.
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Detection of Eye Misalignment Using an HMD with an Eye-tracking Capability
Nagatomo Yoki, Uchida Noriyuki, Ikeda Takuya, Takatsuka Kayoko, Mukunoki Masayuki, Okazaki Naonobu
人工生命とロボットに関する国際会議予稿集 28 863 - 867 2023.2
Language：English Publishing type：Research paper (scientific journal) Publisher：株式会社ALife Robotics
In this study, we implemented the Cover Test, a test method for diagnosing eye misalignment using a head-mounted display with an eye-tracking capability. Specifically, we created a virtual examination environment in a VR space. The eye-tracking technique collected eye movements immediately after the covering or uncovering of the eyes. Thus, we calculated the amount of eye deviation and developed a system to determine the presence and magnitude of strabismus and heterophoria.We assessed the system in the verification experiment by examining the consistency between the judgment results provided by this system and the clinical evaluation approach with the Maddox rod. The result was that we could verify the horizontal eye movements more accurately.
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Detection of Eye Misalignment Using an HMD with an Eye-tracking Capability Reviewed
Nagatomo Y., Uchida N., Ikeda T., Takatsuka K., Mukunoki M., Okazaki N.
Proceedings of International Conference on Artificial Life and Robotics 871 - 875 2023
Publishing type：Research paper (scientific journal) Publisher：Proceedings of International Conference on Artificial Life and Robotics
In this study, we implemented the Cover Test, a test method for diagnosing eye misalignment using a head-mounted display with an eye-tracking capability. Specifically, we created a virtual examination environment in a VR space. The eye-tracking technique collected eye movements immediately after the covering or uncovering of the eyes. Thus, we calculated the amount of eye deviation and developed a system to determine the presence and magnitude of strabismus and heterophoria.We assessed the system in the verification experiment by examining the consistency between the judgment results provided by this system and the clinical evaluation approach with the Maddox rod. The result was that we could verify the horizontal eye movements more accurately.
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リレーアタック耐性とボット耐性の両立を目指したインタラクティブな動画CAPTCHAの提案と評価 Reviewed
油田 健太郎, 臼崎 翔太郎, 山場 久昭, 片山 徹郎, 椋木 雅之, 朴 美娘, 岡崎直宣
情報処理学会論文誌 62 ( 12 ) 1864 - 1878 2021.12
Language：Japanese Publishing type：Research paper (scientific journal)
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Development of a system to detect eye position abnormality based on eye-tracking Reviewed
Uchida N., Takatuka K., Yamaba H., Mukunoki M., Okazaki N.
Journal of Robotics, Networking and Artificial Life 8 ( 3 ) 205 - 210 2021.12
Language：English Publishing type：Research paper (scientific journal) Publisher：Journal of Robotics, Networking and Artificial Life
In previous research, we developed a method to automate the conventional evaluation of eye misalignment (cover test) and distinguish misaligned eyes from their movements. However, this method had the problem that vertical eye movements were affected by the eyelids and eyelashes, and could not be completely detected. To solve this problem, we have developed another method to recognize abnormalities by observing only the movement near the center of the pupil.
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Proposal and evaluation for color constancy CAPTCHA Reviewed
Usuzaki S., Aburada K., Yamaba H., Katayama T., Mukunoki M., Park M., Okazaki N.
Artificial Life and Robotics 26 ( 3 ) 291 - 296 2021.3
Language：English Publishing type：Research paper (scientific journal) Publisher：Artificial Life and Robotics
CAPTCHAs are technologies that distinguish humans and bot to prevent illegal access. Unfortunately, current CAPTCHAs, even the latest Google reCAPTCHA, have already broken with high accuracy. Although the devices, including emphasizing the distortion of the text and adding noise to the image, improve the machine resistance, they may decrease the accessibility of the web page. The purpose of this study is to propose a new CAPTCHA that can decrease the machine resistance while keeping usability. To achieve this purpose, we focused on color constancy. Color constancy is a human’s characteristic that enables humans to recognize the original color of the object by ignoring the effects of illumination light. Color constancy has not been fully reproduced by the program yet. We proposed color constancy CAPTCHA that the user is required to answer an original color of the object in a specified area on the CAPTCHA image with a color filter. In this paper, we created a prototype of CAPTCHA, applied two kinds of color filters, and then evaluated each case for the human success rate, machine success rate, and usability.
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FMD-VS: A virtual sensor to index FMD virus scattering Reviewed
Takatsuka K., Sekiguchi S., Yamaba H., Aburada K., Mukunoki M., Okazaki N.
PLoS ONE 15 ( 9 September ) 2020.9
Language：English Publishing type：Research paper (international conference proceedings) Publisher：PLoS ONE
© 2020 Takatsuka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Foot-and-mouth disease (FMD) models—analytical models for tracking and analyzing FMD outbreaks—are known as dominant tools for examining the spread of the disease under various conditions and assessing the effectiveness of countermeasures. There has been some remarkable progress in modeling research since the UK epidemic in 2001. Several modeling methods have been introduced, developed, and are still growing. However, in 2010 when a FMD outbreak occurred in the Miyazaki prefecture, a crucial problem reported: Once a regional FMD outbreak occurs, municipal officials in the region must make various day-today decisions throughout this period of vulnerability. The deliverables of FMD modeling research in its current state appear insufficient to support the daily judgments required in such cases. FMD model can be an efficient support tool for prevention decisions. It requires being conversant with modeling and its preconditions. Therefore, most municipal officials with no knowledge or experience found full use of the model difficult. Given this limitation, the authors consider methods and systems to support users of FMD models who must make real-time epidemic-related judgments in the infected areas. We propose a virtual sensor, designated “FMD-VS,” to index FMD virus scattering in conditions where there is once a notion of FMD; and (2) shows how we apply the developed FMD-VS technique during an outbreak. In (1), we show our approach to constructing FMD-VS based on the existing FMD model and offer an analysis and evaluation method to assess its performance. We again present the results produced when the technique applied to 2010 infection data from the Miyazaki Prefecture. For (2), we outline the concept of a method that supports the prevention judgment of municipal officials and show how to use FMD-VS.
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Proposal for Rotating 3D Text-based CAPTCHA Using Subjective Contour Reviewed
USUZAKI Shotaro, ABURADA Kentaro, YAMABA Hisaaki, KATAYAMA Tetsuro, MUKUNOKI Masayuki, PARK Mirang, OKAZAKI Naonobu
J103-B ( 8 ) 332 - 343 2020.8
Language：Japanese Publishing type：Research paper (scientific journal)
In this study, we propose a CAPTCHA to improve the usability of the text-based method. This CAPTCHA shows only the side of the 3D characters rotate vertically or horizontally. Users need to input characters rotating in the specified direction to pass it. Humans can recognize the subjective contours of characters but machines cannot recognize them only seeing the shade. Our experiment result shows that the human success rate exceeded the average success rate of the existing method, and the usability is as high as the image-based CAPTCHA. We need to consider more obstruction to reduce attack accuracy against this CAPTCHA.
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An evaluation of the interactive video CAPTCHA method against automated attack Reviewed
Aburada Kentaro, Usuzaki Shotaro, Yamaba Hisaaki, Katayama Tetsuro, Mukunoki Masayuki, Park Mirang, Okazaki Naonobu
IEICE Communications Express 8 ( 12 ) 453 - 457 2019.12
Language：English Publishing type：Research paper (scientific journal) Publisher：一般社団法人 電子情報通信学会
CAPTCHA is designed to detect automated programs (called bots) by requiring them to perform tasks that are easy for humans but difficult for automations. CAPTCHAs are vulnerable to relay attacks in which the challenges are relayed to remote human-solvers. In our previous paper, we proposed an interactive video type CAPTCHA that is strongly resistant to relay attacks. However, a quantitative evaluation of resistance to automated attacks still has not been carried out. Herein, we implement an automated attack for applying to our CAPTCHA and evaluate its resistance to automated attacks. Our results show the robustness of our proposed method against mean shift algorithm.
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Implementation of CAPTCHA suitable for mobile devices Reviewed
Aburada Kentaro, Usuzaki Shotaro, Yamaba Hisaaki, Katayama Tetsuro, Mukunoki Masayuki, Park Mirang, Okazaki Naonobu
IEICE Communications Express 8 ( 12 ) 601 - 605 2019.12
Language：English Publishing type：Research paper (scientific journal) Publisher：一般社団法人 電子情報通信学会
CAPTCHA is a technology designed to prevent automated programs (known as bots) from acquiring access to on-line accounts to send spam mail, manipulate vote numbers in on-line polls, or take other malicious actions. In addition, access to Web services has been incorporated into mobile devices, such as smartphones. However, because most CAPTCHAs are not designed for mobile devices, user-friendly CAPTCHA for mobile devices is required. Thus, we implemented CAPTCHA on mobile devices and evaluated its resistance to bots. Our CAPTCHA showed robustness against bots, with good usability.
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3D-SRGAN: SRGAN の３次元ボクセルモデル超解像への適用 Reviewed
岡 和寿, 椋木 雅之
画像電子学会論文誌 48 ( 4 ) 488 - 496 2019.10
Language：Japanese Publishing type：Research paper (scientific journal)
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CHAMSIN: CaptcHA by caMouflaged StrINg Reviewed
Mukunoki Masayuki, Yamaba Hisaaki, Usuzaki Shotaro, Aburada Kentaro, Katayama Tetsuro, Park Mirang, Okazaki Naonobu
IEICE Communications Express 8 ( 3 ) 55 - 60 2019.3
Language：English Publishing type：Research paper (scientific journal) Publisher：一般社団法人 電子情報通信学会
We propose a new CAPTCHA scheme that uses random dot patterns (RDPs) to prevent highly-developed bots attacks. Human beings can recognize a moving figure filled by a RDP from a background that is filled by another RDP; however, it is impossible to find such figures when they are stationary. Since image recognition by bots is usually carried out frame by frame, it is hard for bots to recognize such moving figures. The proposed CAPTCHA scheme exploits this characteristic. Several experiments were carried out to confirm that the proposed CAPTCHA scheme is usable enough and has enough resistance against bot attacks.
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Interactive Video CAPTCHA for Better Resistance to Automated Attack Reviewed
Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama, Masayuki Mukunoki, Mirang Park, Naonobu Okazaki
2018 Eleventh International Conference on Mobile Computing and Ubiquitous Network 2019.2
Language：English Publishing type：Research paper (international conference proceedings) Publisher：2018 11th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2018
© 2018 IPSJ. A 'Completely Automated Public Turing Test to Tell Computers and Humans Apart' (CAPTCHA) widely used online services so that prevents bots from automatic getting a large of accounts. Interactive video type CAPTCHAs that attempt to detect this attack by using delay time due to communication relays have been proposed. However, these approaches remain insufficiently resistant to bots. We propose a CAPTCHA that combines resistant to automated and relay attacks. In our CAPTCHA, the users recognize a moving object (target object) from among a number of randomly appearing decoy objects and tracks the target with mouse cursor. The users pass the test when they were able to track the target for a certain time. Since the target object moves quickly, the delay makes it difficult for a remote solver to break the CAPTCHA during a relay attack. It is also difficult for a bot to track the target using image processing because it has same looks of the decoys. We evaluated our CAPTCHA's resistance to relay and automated attacks. Our results show that, if our CAPTHCA's parameters are set suitable value, a relay attack cannot be established economically and false acceptance rate with bot could be reduced to 0.01% without affecting human success rate.
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HMD-based Cover Test System for the Diagnosis of Ocular Malalignment Reviewed
Noriyuki Uchida, Kayoko Takatuka, Atsusi Nakazawa, Masayuki Mukunoki, Hisaaki Yamaba, Naonobu Okazaki
Journal of Artificial Life and Robotics, Springer 2019.1
Language：English Publishing type：Research paper (scientific journal)
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A Proposal of New Reading Text CAPTCHA using Random Dot Patterns Reviewed
Hisaaki Yamaba, Shotaro Usuzaki, Kentaro Aburada, Masayuki Mukunoki, Mirang Park and Naonobu Okazaki
Proceedings - 2018 6th International Symposium on Computing and Networking, CANDAR 2018 207 - 212 2018.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2018 6th International Symposium on Computing and Networking, CANDAR 2018
© 2018 IEEE. According to the growth of troubles caused by malicious programs called bots, CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) comes to be an important role in the current information society. CAPTCHA identifies bots from legitimate human users by requiring some questions that are easy for humans to solve but difficult for bots. However, the progress of computing technology such as Optical Character Recognition (OCR) function. bots come to be able to solve present CAPTCHAs. In order to outcome such troublesome bots, more sophisticated CAPTCHA that requires the high cognitive ability of human beings is desired. In this paper, we propose a new CAPTCHA scheme that uses random dot patterns. Human beings can recognize a moving figure filled by a random dot pattern from a background that is filled by another random dot pattern; however, they lose the figure in the background when the figure pauses. Since image recognition by computer programs is usually carried out frame by frame, it is hard for bots to recognize such a moving figure filled by a random dot pattern from another random dot pattern background. The proposed CAPTCHA scheme exploits this characteristic of random dot patterns. This CAPTCHA requires users to answer a text filled by a random dot pattern that is moving on a background also filled by another random dot pattern. Several experiments were carried out to confirm that the proposed CAPTCHA scheme has enough resistance against bot attacks using representative image recognition methods. Results of the experiments showed that the image recognition methods cannot find out the answer text. Other experiments were also carried out to evaluate the usability of the proposed CAPTCHA scheme. The system usability scheme was adopted in the experiments. The obtained score was 89 that means this CAPTCHA scheme has high usability. These results showed that the CAPTCHA scheme is usable enough and has enough resistance against bot attacks.
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Eye Region Detection by Likelihood Combination for Improving Iris Authentication
Thae Su Tun, Masayuki Mukunoki
宮崎大学工学部紀要 47 2018.9
Language：English Publishing type：Research paper (bulletin of university, research institution)
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Image Classification using Collaborative Mean Attraction with Sparse Optimizatio Reviewed
Hiroki Ogihara, Masayuki Mukunoki
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI2018) 2018.5
Language：English Publishing type：Research paper (international conference proceedings)
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Transparent Object Detection Using Convolutional Neural Network Reviewed
May Phyo Khaing, Mukunoki Masayuki
ICBDL 2018 86 - 93 2018.5
Language：English Publishing type：Research paper (international conference proceedings)
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An examination of the interactive video CAPTCHA method to resist relay attack Reviewed
Tatsuda Ryohei, Aburada Kentaro, Yamaba Hisaaki, Katayama Tetsuro, Mukunoki Masayuki, Park Mirang, Okazaki Naonobu
IEICE Communications Express 7 ( 4 ) 136 - 141 2018.4
Language：English Publishing type：Research paper (scientific journal) Publisher：一般社団法人 電子情報通信学会
CAPTCHA is a kind of challenge response test, which is used to distinguish human users from malicious computer program such as bots. However, the attack technique called relay attack as a method to avoid the CAPTCHA has been devised. This attack relays the CAPTCHA challenges to remote human-solvers, let them to decode CAPTCHA challenges. We used delay time that is caused by communications needed in relay attack. Our new CAPTCHA uses this delay time between communications to prevent relay attacks. We constructed an experimental environment in which relay attack can be simulated, made a series of experiments in order to evaluate the performance of the proposed method.
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Tourist Behavior Model Construction Based on Tracks of Tourists Using Regional Environmental Factors and Application Reviewed
Hidekazu Kasahara, Kazunori Tamura, Masaaki Iiyama, Masayuki Mukunoki, Michihiko Minoh
IPSJ Journal 57 ( 5 ) 1411 - 1420 2016.5
Language：Japanese Publishing type：Research paper (scientific journal)
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Locality based discriminative measure for multiple-shot human re-identification Reviewed
Wei Li, Yang Wu, Masayuki Mukunoki, Yinghui Kuang, Michihiko Minoh
Neurocomputing 167 280 - 289 2015.11
Language：English Publishing type：Research paper (scientific journal)
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Clustering scenes in cooking video guided by object access Reviewed
Yuki Matsumura, Atsushi Hashimoto, Shinsuke Mori, Masayuki Mukunoki, Michihiko Minoh
Work Shop on Multimedia Cooking and Eating Activities (CEA2015) 2015.6
Language：English Publishing type：Research paper (international conference proceedings)
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修学旅行事例から見た教育旅行向けモバイル情報サービスの事業モデルと市場戦略-MICE市場での可能性について- Reviewed
笠原秀一，森幹彦, 椋木雅之，美濃導彦
観光情報学会学会誌「観光と情報」 11 ( 1 ) 87 - 98 2015.6
Language：Japanese Publishing type：Research paper (scientific journal)
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Transportation Mode Annotation of Tourist GPS Trajectories Under Environmental Constraints Reviewed
Hidekazu Kasahara, Mikihiko Mori, Masayuki Mukunoki, Michihiko Minoh
Information and Communication Technologies in Tourism 2015, Springer 523 - 535 2015.2
Language：English Publishing type：Research paper (international conference proceedings)
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防犯カメラ映像における条件分割型適合性フィードバックによる特定人物画像検索 Reviewed
井関洋平, 川西康友, 椋木雅之, 美濃導彦
信学論 J98-D ( 1 ) 236 - 249 2015.1
Language：Japanese Publishing type：Research paper (scientific journal)
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Person re-identification by common-near-neighbor analysis Reviewed
Li W., Mukunoki M., Kuang Y., Wu Y., Minoh M.
IEICE Transactions on Information and Systems E97D ( 11 ) 2935 - 2946 2014.11
Language：English Publishing type：Research paper (scientific journal) Publisher：IEICE Transactions on Information and Systems
© 2014 The Institute of Electronics, Information and Communication Engineers. Re-identifying the same person in different images is a distinct challenge for visual surveillance systems. Building an accurate correspondence between highly variable images requires a suitable dissimilarity measure. To date, most existing measures have used adapted distance based on a learned metric. Unfortunately, real-world human image data, which tends to show large intra-class variations and small inter-class differences, continues to prevent these measures from achieving satisfactory re-identification performance. Recognizing neighboring distribution can provide additional useful information to help tackle the deviation of the to-be-measured samples, we propose a novel dissimilarity measure from the neighborhood-wise relative information perspective, which can deliver the effectiveness of those well-distributed samples to the badly-distributed samples to make intra-class dissimilarities smaller than inter-class dissimilarities, in a learned discriminative space. The effectiveness of this method is demonstrated by explanation and experimentation.
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Discriminativ collaborative representation for classification Reviewed
Wu Y., Li W., Mukunoki M., Minoh M., Lao S.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9006 205 - 221 2014.11
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer International Publishing Switzerland 2015. The recently proposed l2-norm based collaborative representation for classification (CRC) model has shown inspiring performance on face recognition after the success of its predecessor — the l1-norm based sparse representation for classification (SRC) model. Though CRC is much faster than SRC as it has a closed-form solution, it may have the same weakness as SRC, i.e., relying on a “good” (properly controlled) training dataset for serving as its dictionary. Such a weakness limits the usage of CRC in real applications because the quality requirement is not easy to verify in practice. Inspired by the encouraging progress on dictionary learning for sparse representation, which can much alleviate this problem, we propose the discriminative collaborative representation (DCR) model. It has a novel classification model well fitting its discriminative learning model. As a result, DCR has the same advantage of being efficient as CRC, while at the same time showing even stronger discriminative power than existing dictionary learning methods. Extensive experiments on nine widely used benchmark datasets for both controlled and uncontrolled classification tasks demonstrate its consistent effectiveness and efficiency.
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Kokura T., Kawanishi Y., Mukunoki M., Minoh M.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 9010 587 - 601 2014.11
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer International Publishing Switzerland 2015. We tackle multiple people tracking across multiple nonoverlapping surveillance cameras installed in a wide area. Existing methods attempt to track people across cameras by utilizing appearance features and spatio-temporal cues to re-identify people across adjacent cameras. @ However, in relatively wide public areas like a shopping mall, since many people may walk and stay arbitrarily, the spatio-temporal constraint is too strict to reject correct matchings, which results in matching errors. Additionally, appearance features can be severely influenced by illumination conditions and camera viewpoints against people, making it difficult to match tracklets by appearance features. These two issues cause fragmentation of tracking trajectories across cameras. We deal with the former issue by selectively relaxing the spatio-temporal constraint and the latter one by introducing a route cue. We show results on data captured by cameras in a shopping mall, and demonstrate that the accuracy of across-camera tracking can be significantly increased under considered settings.
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Improving hough based pedestrian detection accuracy by using segmentation and pose subspaces Reviewed
Vansteenberge J., Mukunoki M., Minoh M.
IEICE Transactions on Information and Systems E97D ( 10 ) 2760 - 2768 2014.10
Language：English Publishing type：Research paper (scientific journal) Publisher：IEICE Transactions on Information and Systems
Copyright © 2014 The Institute of Electronics, Information and Communication Engineers. The Hough voting framework is a popular approach to parts based pedestrian detection. It works by allowing image features to vote for the positions and scales of pedestrians within a test image. Each vote is cast independently from other votes, which allows for strong occlusion robustness. However this approach can produce false pedestrian detections by accumulating votes inconsistent with each other, especially in cluttered scenes such as typical street scenes. This work aims to reduce the sensibility to clutter in the Hough voting framework. Our idea is to use object segmentation and object pose parameters to enforce votes' consistency both at training and testing time. Specifically, we use segmentation and pose parameters to guide the learning of a pedestrian model able to cast mutually consistent votes. At test time, each candidate detection's support votes are looked upon from a segmentation and pose viewpoints to measure their level of agreement. We show that this measure provides an efficient way to discriminate between true and false detections. We tested our method on four challenging pedestrian datasets. Our method shows clear improvements over the original Hough based detectors and performs on par with recent enhanced Hough based detectors. In addition, our method can perform segmentation and pose estimation as byproducts of the detection process.
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Kasahara H., Kurumatani K., Mori M., Mukunoki M., Minoh M.
Information Technology and Tourism 14 ( 3 ) 197 - 217 2014.9
Language：English Publishing type：Research paper (scientific journal) Publisher：Information Technology and Tourism
© 2014, Springer-Verlag Berlin Heidelberg. The recent earthquake in Japan showed that tourists cannot access evacuation information and the families of tourists experienced problems when accessing safety information related to tourists. Given these problems, we consider two issues related to information provision in disaster situations. The first issue is the lack of evacuation information for tourists. The second issue is the difficulty of confirming the safety of tourists and sharing their safety information with relevant people, including the tourist’s family. The present study focuses on developing a tourism information system to solve these issues. We refer to this system as an Educational Trip Support System (ETSS). The research subject is a school trip, which is a representative type of group tour that occurs in Japan. The objectives of the ETSS are to help students to escape to an evacuation area rapidly by providing evacuation information and to share safety confirmations with relevant people during disaster situations. We assessed the effectiveness based on a field test in a disaster-simulated situation and quantitative surveys. The major contributions of this study include (1) a description of a mobile application system for confirming safety during school trips and sharing information with relevant people, (2) a method to facilitate the rapid evacuation of students that saves time and reduces their concerns about the situation, (3) detailed evaluations of the performance obtained using ETSS.
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Can feature-based inductive transfer learning help person re-identification? Reviewed
Wu Y., Li W., Minoh M., Mukunoki M.
2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings 2812 - 2816 2013.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
Person re-identification concerns about the problem of recognizing people across space (captured by different cameras) and/or over time gaps. Though recently the literature on it grows rapidly, all the proposed solutions have treated it as a normal classification or ranking problem. In this paper, however, we argue that it is in fact a natural transfer learning problem, thus it's valuable and also necessary to investigate how the progress on transfer learning could benefit the research on it. We present so far the first study on justifying the effectiveness of a representative transfer learning methodology: feature-based inductive transfer learning, for person re-identification. Extensive experiments on standard datasets with typical methods result in several important findings. © 2013 IEEE.
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Collaboratively Regularized Nearest Points for Set Based Recognition Reviewed
Yang Wu, Michihiko Minoh, Masayuki Mukunoki
4th British Machine Vision Conference (BMVC2013) 2013.9
Language：English Publishing type：Research paper (international conference proceedings)
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Riemannian Set-level Common-Near-Neighbor Analysis for Multiple-shot Person Re-identification Reviewed
Wei Li, Yang Wu, Yasutomo Kawanishi,Masayuki Mukunoki, Michihiko Minoh
IAPR International Conference on Machine Vision Application(MVA2013) 2013.5
Language：English Publishing type：Research paper (international conference proceedings)
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Combined Object Detection and Segmentation Reviewed
Jarich Vansteenberge, Masayuki Mukunoki, Michihiko Minoh
International Journal of Machine Learning and Computing(IJMLC), Vol.3(1), pp.60-64, DOI: 10.7763/IJMLC.2013.V3.273, ISSN: 2010-3700 2013.2
Language：English Publishing type：Research paper (international conference proceedings)
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Coupled metric learning for single-shot versus single-shot person reidentification Reviewed
Li, Wei; Wu, Yang; Mukunoki, Masayuki; Minoh, Michihiko
OPTICAL ENGINEERING 52 ( 2 ) 2013.2
Language：English Publishing type：Research paper (scientific journal)
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Locality based discriminative measure for multiple-shot person re-identification Reviewed
Li W., Wu Y., Mukunoki M., Minoh M.
2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013 312 - 317 2013
Language：English Publishing type：Research paper (international conference proceedings) Publisher：2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013
Multiple-shot person re-identification tackles the problem to build the correspondences between sets of human images obtained from distributed cameras. It is challenging due to large within-class variations and small between-class differences, caused by the changing of human appearance and environment. Existing methods for addressing this issue include designing the representation to capture the within-set correlation, or crafting the measure to explore the between-set separation. This paper proposes a novel set based matching model called 'Locality Based Discriminative Measure (LBDM)', in which the discriminative potentiality of a new set-to-set distance is exploited by using the learned local metric field. As experimentally demonstrated, the proposal remarkably outperforms state-of-the-art schemes on public benchmark datasets. © 2013 IEEE.
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Locality-constrained collaborative sparse approximation for multiple-shot person re-identification Reviewed
Wu Y., Mukunoki M., Minoh M.
Proceedings - 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 140 - 144 2013
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013
Person re-identification is becoming a hot research topic due to its academic importance and attractive applications in visual surveillance. This paper focuses on solving the relatively harder and more importance multiple-shot re-identification problem. Following the idea of treating it as a set-based classification problem, we propose a new model called Locality-constrained Collaborative Sparse Approximation (LCSA) which is made to be as efficient, effective and robust as possible. It improves the very recently proposed Collaborative Sparse Approximation (CSA) model by introducing two types of locality constraints to enhance the quality of the data for collaborative approximation. Extensive experiments demonstrate that LCSA is not only much better than CSA in terms of effectiveness and robustness, but also superior to other related methods. © 2013 IEEE.
DOI： 10.1109/ACPR.2013.14
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Robust object recognition via third-party collaborative representation Reviewed
Wu Y., Minoh M., Mukunoki M., Lao S.
Proceedings - International Conference on Pattern Recognition 3423 - 3426 2012.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - International Conference on Pattern Recognition
A simple and effective method is proposed for object recognition via collaborative representation with ridge regression. Different from existing sparse representation and collaborative representation based approaches, the proposal does not need extensive training samples for each testing class and it is robust to localization errors and large within-class variations, thus being applicable to various real-world object recognition tasks instead of handling only the well-controlled face recognition problem. Its discriminative power is explored from a third-party dataset which can be different from the training and testing datasets, therefore, it enables using an existing dictionary for testing new data without time-consuming data annotation and model re-training. As an example, the proposal is extensively tested on the representative and very challenging task of person re-identification, defining novel state-of-the-art results on widely adopted benchmark datasets using only simple and common features. © 2012 ICPR Org Committee.
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Common-near-neighbor analysis for person re-identification Reviewed
Li W., Wu Y., Mukunoki M., Minoh M.
Proceedings - International Conference on Image Processing, ICIP 1621 - 1624 2012.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - International Conference on Image Processing, ICIP
Person re-identification tackles the problem whether an observed person of interest reappears in a network of cameras. The difficulty primarily originates from few samples per class but large amounts of intra-class variations in real scenarios: illumination, pose and viewpoint changes across cameras. So far, proposals in the literature have treated this either as a matching problem focusing on feature representation or as a classification/ranking problem relying on metric optimization. This paper presents a new way called Common-Near-Neighbor Analysis, which to some extent combines the strengths of these two methodologies. It analyzes the commonness of the near neighbors of each pair of samples in a learned metric space, measured by a novel rank-order based dissimilarity. Our method, using only color cue, has been tested on widely-used benchmark datasets, showing significant performance improvement over the state-of-the-art. © 2012 IEEE.
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Collaborative sparse approximation for multiple-shot across-camera person re-identification Reviewed
Wu Y., Minoh M., Mukunoki M., Li W., Lao S.
Proceedings - 2012 IEEE 9th International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2012 209 - 214 2012.11
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2012 IEEE 9th International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2012
In this paper we propose a simple and effective solution to the important and challenging problem of acrosscamera person re-identification. We focus on the common case in video surveillance where multiple images or video frames are available for each person. Instead of exploring new features, the proposed approach aims at making a better use of such images/frames. It builds a collaborative representation over all the gallery images (of known person individuals) to best approximate the query images (containing an unknown person) via affine combinations. The approximation is measured by the nearest point distance between the two affine hulls constructed by the query images and gallery images, respectively. By enforcing the sparsity of the samples used for approximating the two nearest points, the relative importance of the gallery images belonging to different persons has the ability to reveal the identity of the querying person. Extensive experiments on public benchmark datasets demonstrate that the proposed approach greatly outperforms the state-of-the-art methods. © 2012 IEEE.
DOI： 10.1109/AVSS.2012.21
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Students' posture sequence estimation using spatio-temporal constraints Reviewed
Mukunoki M., Yoshitsugu K., Minoh M.
Communications in Computer and Information Science 298 CCIS ( PART 2 ) 415 - 424 2012.11
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Communications in Computer and Information Science
We propose a method for estimating the students' posture sequence in classroom from video footage by computer automatically. A posture sequence is a time-series of student's postures during a lecture and a posture of a student is described by a set of his head, body trunk (torso) and hands/arms states, which we call the body part states. The detection of body parts from video footage has many errors. To cope with the errors, we introduce spatio-temporal constraints, in which we propagate the belief of postures through a given time interval with considering the confidence of observation. Through this propagation, we can revise the erroneous detection results and estimate an appropriate posture sequence. In the experiment, we apply our proposed method to a real lecture, and show that our method can improve the accuracy of posture sequence estimation. © 2012 Springer-Verlag Berlin Heidelberg.
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Set based discriminative ranking for recognition Reviewed
Wu Y., Minoh M., Mukunoki M., Lao S.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7574 LNCS ( PART 3 ) 497 - 510 2012.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Recently both face recognition and body-based person re-identification have been extended from single-image based scenarios to video-based or even more generally image-set based problems. Set-based recognition brings new research and application opportunities while at the same time raises great modeling and optimization challenges. How to make the best use of the available multiple samples for each individual while at the same time not be disturbed by the great within-set variations is considered by us to be the major issue. Due to the difficulty of designing a global optimal learning model, most existing solutions are still based on unsupervised matching, which can be further categorized into three groups: a) set-based signature generation, b) direct set-to-set matching, and c) between-set distance finding. The first two count on good feature representation while the third explores data set structure and set-based distance measurement. The main shortage of them is the lack of learning-based discrimination ability. In this paper, we propose a set-based discriminative ranking model (SBDR), which iterates between set-to-set distance finding and discriminative feature space projection to achieve simultaneous optimization of these two. Extensive experiments on widely-used face recognition and person re-identification datasets not only demonstrate the superiority of our approach, but also shed some light on its properties and application domain. © 2012 Springer-Verlag.
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Learning to Estimate Slide Comprehension in Classrooms with Support Vector Machines Reviewed
Pattanasri N., Mukunoki M., Minoh M.
IEEE Transactions on Learning Technologies 5 ( 1 ) 52 - 61 2012.1
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE Transactions on Learning Technologies
Comprehension assessment is an essential tool in classroom learning. However, the judgment often relies on experience of an instructor who makes observation of students' behavior during the lessons. We argue that students should report their own comprehension explicitly in a classroom. With students' comprehension made available at the slide level, we apply a machine learning technique to classify presentation slides according to comprehension levels. Our experimental result suggests that presentation-based features are as predictive as bag-of-words feature vector which is proved successful in text classification tasks. Our analysis on presentation-based features reveals possible causes of poor lecture comprehension. © 2012, IEEE
DOI： 10.1109/TLT.2011.22
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“ 修学旅行における生徒の満足度向上”
笠原秀一,森幹彦,椋木雅之,美濃導彦
観光情報学会第6 回研究発表会， 2012-12 2012
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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“ 非一様な照明変動環境下におけるカメラ間人物対応付けのため の人物色補正”
川西康友,福井啓允,椋木雅之,美濃導彦
画像の認識・理解シンポジウム（MIRU2012），2012-08． 2012
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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“ 観光情報基盤により安全安心な旅行を実現する街づくりのデザイン”
笠原秀一,森幹彦,椋木雅之,美濃導彦
Design シンポジウム2012，2012-10 2012
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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Optimizing mean reciprocal rank for person re-identification Reviewed
Wu Y., Mukunoki M., Funatomi T., Minoh M., Lao S.
2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011 408 - 413 2011.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
Person re-identification is one of the most challenging issues in network-based surveillance. The difficulties mainly come from the great appearance variations induced by illumination, camera view and body pose changes. Maybe influenced by the research on face recognition and general object recognition, this problem is habitually treated as a verification or classification problem, and much effort has been put on optimizing standard recognition criteria. However, we found that in practical applications the users usually have different expectations. For example, in a real surveillance system, we may expect that a visual user interface can show us the relevant images in the first few (e.g. 20) candidates, but not necessarily before all the irrelevant ones. In other words, there is no problem to leave the final judgement to the users. Based on such an observation, this paper treats the re-identification problem as a ranking problem and directly optimizes a listwise ranking function named Mean Reciprocal Rank (MRR), which is considered by us to be able to generate results closest to human expectations. Using a maximum-margin based structured learning model, we are able to show improved re-identification results on widely-used benchmark datasets. © 2011 IEEE.
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把持の順序と外見の変化モデルを利用した調理作業における食材追跡 Reviewed
橋本敦史;森直幸;舩冨卓哉;山肩洋子;椋木雅之;角所考;美濃導彦
電子情報通信学会論文誌 A J94-A ( 7 ) 509 - 518 2011.7
Language：Japanese Publishing type：Research paper (scientific journal)
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ＴｅｘＣｕｔ：ＧｒａｐｈＣｕｔを用いたテクスチャの比較による背景差分 Reviewed
橋本敦史;舩冨卓哉;中村和晃;椋木雅之;美濃導彦
電子情報通信学会論文誌 D J94-D ( 6 ) 1007 - 1016 2011.6
Language：Japanese Publishing type：Research paper (scientific journal)
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Tracking food materials with changing their appearance in food preparing Reviewed
Hashimoto A., Mori N., Funatomi T., Mukunoki M., Kakusho K., Minoh M.
Proceedings - 2010 IEEE International Symposium on Multimedia, ISM 2010 248 - 253 2010.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2010 IEEE International Symposium on Multimedia, ISM 2010
This paper describes our work in computer vision to track food materials in the food preparation process. Tracking such food materials is difficult, because they are often hidden when moved by hand. Furthermore, their appearance may change in hand when they are cut or peeled. For tracking these objects in such situations, we propose a novel method that matches an object on a cooking table to one grasped in the past. We use the following three criteria to match the objects even when they are cut or peeled: the similarity in their appearance, the validity of their change in appearance, and the grasped order. We experimentally evaluated our method by applying it to the scenes of cutting and peeling food materials. As a result, we achieved an accuracy of 83.6% in matching the objects. © 2010 IEEE.
DOI： 10.1109/ISM.2010.43
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Privacy-protected camera for the sensing web Reviewed
Mitsugami I., Mukunoki M., Kawanishi Y., Hattori H., Minoh M.
Communications in Computer and Information Science 81 PART 2 622 - 631 2010.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Communications in Computer and Information Science
We propose a novel concept of a camera which outputs only privacy-protected information; this camera does not output captured images themselves but outputs images where all people are replaced by symbols. Since the people from this output images cannot be identified, the images can be opened to the Internet so that we could observe and utilize the images freely. In this paper, we discuss why the new concept of the camera is needed, and technical issues that are necessary for implementing it. © Springer-Verlag Berlin Heidelberg 2010.
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TexCut: GraphCut を用いたテクスチャの比較による背景差分の検討
橋本敦史, 中村和晃, 舩冨卓哉, 椋木雅之, 美濃導彦
PRMU 2010.11
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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Background image generation by preserving lighting condition of outdoor scenes Reviewed
Y. Kawanishi; I. Mitsugami; M. Mukunoki; M. Minoh
Procedia - Social and Behavioral Sciences 2 ( 1 ) 129 - 136 2010
Language：English Publishing type：Research paper (scientific journal)
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Camera model for inverse perspective Reviewed
M. Baba; M. Yamamoto; M. Mukunoki; N. Asada
ACM SIGGRAPH ASIA 2010 Posters, SA\\'10 2010
Language：English Publishing type：Research paper (international conference proceedings)
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“姿勢事例の獲得とその補完による手の 計測形状の姿勢操作”
大内田裕胤,籔内智浩,舩冨卓哉,飯山将晃,椋木雅之,美濃導彦
画像の認識・理解シンポジウム（MIRU2010），2010-07． 2010
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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ComprehEnRank: Estimating comprehension in classroom by absorbing random walks on a cognitive graph Reviewed
Pattanasri N., Mukunoki M., Minoh M.
International Conference on Information and Knowledge Management, Proceedings 1769 - 1772 2009.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：International Conference on Information and Knowledge Management, Proceedings
This paper develops a graph-theoretic framework for estimating comprehension in classroom. To deal with imprecise data gathered in classroom, we propose multi-step comprehension propagation over a semantic graph. Random walks on the graph measure students' comprehension with probabilities absorbed at student nodes. Copyright 2009 ACM.
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Background Image Generation Keeping Lighting Condition of Outdoor Scenes Reviewed
Yasutomo Kawanishi, Ikuhisa Mitsugami, Masayuki Mukunoki, Michihiko Minoh
The 1st International Conference on Security Camera Network, Privacy Protection and Community Safety (SPC2009) Best Paper Award受賞 2009
Language：English Publishing type：Research paper (international conference proceedings)
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Estimating Reflectance of a Real Object using Bump Model Reviewed
Baba M., Mukunoki M., Asada N.
Journal of the Institute of Image Electronics Engineers of Japan 36 ( 4 ) 362 - 370 2007.1
Language：English Publishing type：Research paper (scientific journal) Publisher：Journal of the Institute of Image Electronics Engineers of Japan
Reflectance of objects plays an important role in image synthesis. Many reflection models have been proposed to describe the reflectance of real objects. To synthesize a realistic image of real objects, it is required to measure parameters of reflection models from real images. Another important issue is modeling the bump parameters of a surface. In this paper, we propose a method to measure a roughness of the surface from real images of real objects. First, we define a bump model to represent the roughness of the surface. Next, we improve the reflection models for both specular and diffuse. Then, we measure reflectance properties from real images, and show realistic images of real objects by using improved reflection models and bump model. © 2007, The Institute of Image Electronics Engineers of Japan. All rights reserved.
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Simultaneous estimation of reflectance parameters from images Reviewed
Miura S., Baba M., Mukunoki M., Asada N.
ACM SIGGRAPH 2006 Research Posters, SIGGRAPH 2006 2006.7
Language：English Publishing type：Research paper (international conference proceedings) Publisher：ACM SIGGRAPH 2006 Research Posters, SIGGRAPH 2006
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Table form document analysis based on the document structure grammar Reviewed
Amano A., Asada N., Mukunoki M., Aoyama M.
International Journal on Document Analysis and Recognition 8 ( 2-3 ) 201 - 213 2006.6
Language：English Publishing type：Research paper (scientific journal) Publisher：International Journal on Document Analysis and Recognition
Structure analysis of table form documents is an important issue because a printed document and even an electronic document do not provide logical structural information but merely geometrical layout and lexical information. To handle these documents automatically, logical structure information is necessary. In this paper, we first analyze the elements of the form documents from a communication point of view and retrieve the grammatical elements that appear in them. Then, we present a document structure grammar which governs the logical structure of the form documents. Finally, we propose a structure analysis system of the table form documents based on the grammar. By using grammar notation, we can easily modify and keep it consistent, as the rules are relatively simple. Another advantage of using grammar notation is that it can be used for generating documents only from logical structure. In our system, documents are assumed to be composed of a set of boxes and they are classified as seven box types. Then the box relations between the indication box and its associated entry box are analyzed based on the semantic and geometric knowledge defined in the document structure grammar. Experimental results have shown that the system successfully analyzed several kinds of table forms. © Springer-Verlag 2005.
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A unified camera calibration using geometry and blur of feature points Reviewed
M. Baba; M. Mukunoki; N. Asada
Proceedings - International Conference on Pattern Recognition 1 816 - 819 2006
Language：Japanese Publishing type：Research paper (international conference proceedings)
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A new camera calibration method taking blur effects into account Reviewed
Baba M., Mukunoki M., Asada N.
ACM SIGGRAPH 2005 Sketches, SIGGRAPH 2005 2005.7
Language：English Publishing type：Research paper (international conference proceedings) Publisher：ACM SIGGRAPH 2005 Sketches, SIGGRAPH 2005
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Reflectance estimation of sparkle in metallic paints Reviewed
Baba M., Miura S., Mukunoki M., Asada N.
ACM SIGGRAPH 2005 Posters, SIGGRAPH 2005 2005.7
Language：English Publishing type：Research paper (international conference proceedings) Publisher：ACM SIGGRAPH 2005 Posters, SIGGRAPH 2005
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3D model generation from image sequences using global geometric constraint Reviewed
M. Mukunoki; K. Yasuda; N. Asada
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3804 LNCS 470 - 477 2005
Language：English Publishing type：Research paper (international conference proceedings)
DOI： 10.1007/11595755_57
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Retrieval of images using pixel based object models Reviewed
Mukunoki M., Minoh M., Ikeda K.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 945 557 - 566 2005
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer Verlag 2005. We apply our Pixel-based object labeling method tothe problem of indexing images. Our method is a means to assign an object label to each pixel in out-door scenes. It is suitable for automatic object labeling and applicable to automatic indexing problems. The recognition rate of our method is about 77%. To apply our method to the problem of indexing, we introduce a pictorial query method for retrieva.We conducted some retrieval experiments, and examined the usability of our method to the indexing problem.
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Large object shape recovery from uncalibrated camera motion by non-linear optimization Reviewed
Asada N., Mukunoki M., Migita T., Aoyama M.
Sixth IASTED International Conference on Signal and Image Processing 151 - 156 2004.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Sixth IASTED International Conference on Signal and Image Processing
3D recovery of object shape and camera motion from 2D image sequence is formulated as a non-linear optimization problem. Such a non-linear approach ensures the most precise solution, but it involves computational difficulties, i.e. complexity and instability. This paper describes a practical procedure to solve the non-linear optimization problem for object shape and camera motion recovery. First, we discuss the imaging model for large objects such as buildings; one shot and pseudo wide angle models, where the camera motion is modeled as a uniform motion along circular path with gazing at the center. Then, the generalized initial values for circular motion is proposed and "mean appearance ratio (MAR)" of feature points is defined as a measure of stability. Experimental results with synthetic images show that 3D recovery was stably performed from image sequences with MAR over 15%, quasi-stable with over 8.5% for one shot model, and stable with over 10.3%, quasi-stable with over 4. 4% for pseudo wide angle model. 3D shape and motion using real images were recovered successfully from MAR 17% for one shot model and 6% for pseudo wide angle one. These results have demonstrated the robustness of the generalized initial values and effectiveness of MAR for large object shape from uncalibrated camera motion problem.
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Modification table form generation system based on the form recognition Reviewed
Amano A., Asada N., Mukunoki M.
Proceedings - International Conference on Pattern Recognition 2 659 - 662 2004.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - International Conference on Pattern Recognition
As there exist large number of both printed and electronical documents of table form, it is very important to provide their handling system. The system should provide capability of generating, modifying or filling in to the form only with logical manipulation. In this paper, we propose a system which can extract the structure of the form, and modify it logically without considering layout information, and finally generate modified form layout. The system is based on our table form analysis method and table form representation language (TFML). Experimental results show that the system can generate practical layouts for the modified documents.
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Estimating roughness parameters of an object's surface from real images Reviewed
Baba M., Mukunoki M., Asada N.
ACM SIGGRAPH 2004 Posters, SIGGRAPH 2004 2004.8
Language：English Publishing type：Research paper (international conference proceedings) Publisher：ACM SIGGRAPH 2004 Posters, SIGGRAPH 2004
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Shadow removal from a real image based on shadow density Reviewed
Baba M., Mukunoki M., Asada N.
ACM SIGGRAPH 2004 Posters, SIGGRAPH 2004 2004.8
Language：English Publishing type：Research paper (international conference proceedings) Publisher：ACM SIGGRAPH 2004 Posters, SIGGRAPH 2004
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“Shadow Removal from a Real Image Based on Color Clustering” Reviewed
Baba M., Mukunoki M., Asada N.
Journal of the Institute of Image Electronics Engineers of Japan 33 ( 3 ) 531 - 538 2004.1
Language：Japanese Publishing type：Research paper (international conference proceedings) Publisher：Journal of the Institute of Image Electronics Engineers of Japan
This paper proposes a method to remove shadows from a real image based on RGB color space analysis. The algorithm consists of five steps. First, all pixel colors are mapped on the RGB space, and the color distribution is segmented by using clustering method. Second, a pair of clusters that are almost aligned on a color vector is found. We consider the darker cluster as shadow area and the lighter as sunshine one. Next, we perform the color adjustment between them by modifying the direction of shadow cluster to be that of sunshine one. Fourth, the color average and variance of the shadow cluster are adjusted to be the same as those of the sunshine one. Finally, we apply a smoothing filter to correct the boundary discontinuity that sometimes occurs around fuzzy boundary between shadow and sunshine areas. Experimental results show that our algorithm worked successfully inreal situations. © 2004, The Institute of Image Electronics Engineers of Japan. All rights reserved.
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Controlling a Camera with Minimized Camera Motion Changes under the Constraint of a Planned Camera-work Reviewed
Yasutaka ATARASHI,Yoshinari KAMEDA,Masayuki MUKUNOKI,Koh KAKUSHO,Michihiko MINOH,Katsuo IKEDA
International Workshop on Pattern Recognition and Understanding for Visual Information Media in Cooperation with ACCV 2002 2002
Language：English Publishing type：Research paper (international conference proceedings)
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Classification of rawmaterial sports videos for broadcasting using color and edge features Reviewed
Mukunoki M., Bettini M., Assfalg J., Del Bimbo A.
Proceedings - IEEE International Conference on Multimedia and Expo 1187 - 1190 2001
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - IEEE International Conference on Multimedia and Expo
We discuss the method to classify raw material sports videos for broadcasting. Because the raw material sports videos sometimes do not edited, we cannot use the knowledge on edited videos. We use the color and edge features and evaluate whether we can classify the sports videos with those features. We also introduce "player" and "audience" class apart from each sport class to improve the classification results.
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Detection of the indicated area with an indication stick Reviewed
Sakiyama T., Mukunoki M., Ikeda K.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1948 480 - 487 2000
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
© Springer-Verlag Berlin Heidelberg 2000. This paper describes a detection method of indication action and the corresponding indicated area with a stick. In human communication, there exists ambiguity of indication action, so we need some useful knowledge about indication action. We propose a detection method of the indicated area based on the knowledge which we clarify by means of observation of some lectures. We formulate a potential value of intentional indication action of an instant, and cast the value for printed area using a weighted vote method. An experimental result shows that 85 percents of indication actions are correctly detected.
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Classification method of images based on composition and its application to image retrieval Reviewed
Maeda S., Mukunoki M., Ikeda K.
International Conference on Multimedia Computing and Systems -Proceedings 2 240 - 244 1999
Language：English Publishing type：Research paper (international conference proceedings) Publisher：International Conference on Multimedia Computing and Systems -Proceedings
We propose a visual query method for image retrieval, in which the user expresses the composition of the target image by selecting one of the composition types presented by the system, and also propose an image classification method to derive composition types from an image database. From the viewpoint of communication between the system and its user, we point out the problem of visual query methods using concrete images as queries. Though suited to convey visual image properties, they grow the ambiguity in the system's interpretation of queries. To manage this tradeoff, we implemented our methods in a prototype system and derived composition types from an image database to show how our query method works in image retrieval.