Presentations -
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Motion History and Shape Orientation Based Human Action Analysis International conference
Swe Nwe Nwe Htun, Thi Thi Zin
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
In recent decades, many research works focused on the considerations of falling and post-falling event analysis in the aspect of image processing technology to meet the consumer perspective of users. In this paper, the more informative considerations of human action analysis are developed for the prior state of fall or normal actions. In doing so, the effective background subtraction namely the Mixture of Gaussian with Low-Rank Matrix Factorization model is used to obtain robust and adaptive foreground from the practical video sequences. Then, the spatial-temporal bilateral grid for video sequences is constructed by using a standard graph cut theory to improve the cleaned foreground in order to detect the moving/motionless object region. Then, human actions are analyzed by employing motion history and shape orientation using the approximated ellipse method. The experiments are conducted on publicly available video sequences and our simulated video sequences.
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Image-Based Feeding Behavior Detection for Dairy Cow International conference
K. Shiiya, F. Otsuka, Thi Thi Zin, I. Kobayashi
2019 IEEE 8th Global Conference on Consumer Electronics (GCCE 2018) (Senri Life Science Center, Osaka, Japan) IEEE Consumer Electronics Society
Event date： 2019.10.15 - 2019.10.18
Language：English Presentation type：Oral presentation (general)
Venue：Senri Life Science Center, Osaka, Japan
Feeding behavior is an important source of information to know cow's health status, because it is influenced by the feeding environment, cow's physiological changes and health conditions. However, a cow feeds intermittently throughout the day, it is difficult to measure feeding time by visual measurement at field level. In this paper we propose a measurement method of feeding frequency and feeding time for dairy cow, by detecting the feeding behavior by non-contact using a camera.
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ICTを活用した牛のモニタリングシステムの開発に関する研究 Invited
Thi Thi Zin、小林 郁雄、椎屋 和久、Pyke Tin、堀井 洋一郎、濱 裕光
2019年度電気・情報関係学会九州支部連合大会（第72回連合大会） (九州工業大学 戸畑キャンパス) 電気・情報関係学会
Event date： 2019.9.27 - 2019.9.28
Language：Japanese Presentation type：Oral presentation (general)
Venue：九州工業大学 戸畑キャンパス
高齢化、大規模化する現代の畜産で、24 時間 365 日に
わたり家畜の健康管理を適切に行い、異常や変化に留意
し続けながら経営を継続することは容易でない。本研究で
は、家畜生産性の改善と地域活性化の実現を最終目的と
する。人の監視・見守りの分野で開発された非接触・非侵
襲センサ情報の解析アルゴリズムを独自の手法で応用し、
生産者の負担を大幅に軽減しながら家畜の状態を 24 時間
監視できるシステムを開発する。具体的には、畜産農家か
らの強い要望がある、ボディコンディションスコア（BCS：Body Condition Score）の評価、発情検知、分娩過程の管理、個体識別、異常検知等を可能とするシステムの開発を目指す。 -
Gemological Analysis of Some Rare Gemstones from Mogok Area, Mandalay Region International conference
Htin Lynn Aung, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Mogok has long been noted as a supplier of various gemstones over the past decades. The principal gemstones are ruby, sapphire and spinel. Nowadays, fabulous rare gemstones from Mogok are being sold in foreign markets. This area is mainly composed of igneous and metamorphic rocks. Exceptionally rare gemstones are also discovered and they are johachidolite, poudretteite, thorite, etc. The fantastic occurrences of rare gemstones provoke attraction and well attention to mineralogists and gemmologists. Most of the rare gemstones in the present research work are studied from gems dealers from Mogok. Other rare samples are recorded and studied in the favour of the gems collectors. The data on primary occurrence of these rare gemstones are still uncertain and further investigation should be required. In the Mogok area, these rare minerals recovered from alluvial, eluvial, residual deposits along the river side, hill slope, flat plains and low lying area. Economically, rare gemstones are highly important for both local and foreign gem markets. Some gemstones are important economically as well as technologically for its composition, such as thorite and beryl which are used in space and aeronautical purposes. Most of the rare gemstones are valuable for its rarity and collected as museum pieces and collector’s stones. Thus, they are invaluable.
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Robust Tracking of Cattle Using Super Pixels and Local Graph Cut for Monitoring Systems International conference
Y. Hashimoto, H. Hama, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Development of a cattle monitoring system by non-contact and non-invasive methods to improve productivity is a strong desire from large or small scale farmers with aging society. As one of elemental technologies, we will focus on estimating the position of cattle for detecting characteristic behaviors using video camera frames. To do so, cattle region must be extracted. Because Japanese black cattle move slowly in general, region extraction by the inter-frame difference is difficult. At the same time, since the skin is similar to soil in color, region extraction is not so easy, even if background subtraction is used. Here, ROI (Region of Interest) and Scribbles (foreground, background) are manually set at first, and SP (Super Pixels) and LGC (Local Graph Cut) are adopted to extract robustly cattle regions. The movement of cattle is estimated from change of the gravity center of the extracted cattle region. We propose a new method to update ROI and Scribbles according to the change. The tracking of cattle walking normally was successfully continued until a part of the body was framed out. Without proposed updating, there are many cases in which tracking fails within a few frames. The effectiveness of the proposed method has been confirmed through the experimental results.
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A Correlated Random Walk Modeling Method for Dairy Cow Inter-calving Body Condition Score Pattern Analysis International conference
Thi Thi Zin, Pyke Tin, H. Hama
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In this paper, we shall explore and examine the potentials of a correlated random walk model to describe the body condition score pattern change between two successive calving time intervals in dairy cows. The random walk model due to its stochastic natures can fully describe the pattern and quantify its characteristics composed of the sum of random variables derived from milk yields, feeding intakes and transition periods in the body energy reserves changes. In order to achieve optimality of dairy farm management systems, the key indicator is individual cow body conditions score for maintaining target score in corresponding periods such as a few weeks after calving, early lactation, mid lactation and dry periods. Thus, the dairy cow energy reserves problem of within-the-two successive calving events, the body condition score fluctuations is critical especially at the time of calving, with improvements in production. However, a little has known the statistical and probabilistic tools for relating the body condition score pattern change and milk production, feeding management and animal health during the inter-calving periods. In this concern, we shall formulate the problem of energy reserves in dairy cow body, as a correlated random walk model in which inputs (feed intakes), outputs (mike produced) and the body condition score (energy research storage) are used as random variables. Utilizing an incomplete Gamma and the univariate normal distribution functions for the marginal and joint distributions of the inputs and outputs in the random walk model, the expected change patterns in body condition scores with respect to time are derived and analyzed. Then we provide some simulation results by using the estimated parameters for inputs and outputs derived from real life dataset. These results shows that the proposed approach and method are promising in line with precision dairy farming.
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Offline Handwritten Character Recognition System on Tablet Mobile International conference
Thi Thi Zin, T. Otsuzuki
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
Handwritten character recognition is one of the most challenging and important research areas in the field of image processing since there is a variation of same character due to the change of fonts and sizes in handwriting especially by early learners in formal and non-formal basic education. The early school age children in general have diversity in handwriting style, variation in angle, size and shape of characters making the problems of character recognition more difficult. In recent years, due to international efforts, the number of enrolled students worldwide has been increasing year by year. However, due to lack of teachers, many children cannot access high quality education. Therefore, in this paper, offline character recognition for handwritten characters written on tablet was proposed. This paper can be expected to support education for preschool children. This proposed method firstly performs character segmentation process on words acquired from the tablet. In the feature extraction proposes Histogram of Oriented Gradients (HOG) and Bag-of-Visual Words (BOVW) are used. Support Vector Machine (SVM) is applied in classification process. Some experimental results are shown to confirm the proposed method.
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A Study on Detecting Violence Using Image Processing Technology International conference
S. Misawa, Thi Thi Zin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In recent years, many security cameras have been installed for crime prevention in downtown areas and public facilities. These cameras have greatly contributed to crime prevention and criminal identification. However, the large number of installed cameras is problematic due to difficulties in manually monitoring and detecting violence and crime in real time, as well as in finding specific video footage recording the incidents. This paper describes the use of the background difference method in extracting human regions from data obtained using security cameras. In addition, the paper describes a method of detecting violence using features such as speed and moving distance after contact. Using video footage from seven data sets, these methods have been experimentally evaluated, confirming a high detection rate for incidents involving two people side by side.
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Object Tracking Based on Color Features from Key Frames International conference
Mie Mie Tin, Mie Mie Khin, Nyein Nyein Myo, Thi Thi Zin, Pyke Tin
The 14th International Conference on Innovative Computing, Information and Control (ICICIC2019) (Soongsil University, Seoul, Korea) ICIC International
Event date： 2019.8.26 - 2019.8.29
Language：English Presentation type：Oral presentation (general)
Venue：Soongsil University, Seoul, Korea
In the world, everybody needs to protect their life to save and to prevent from dangerous case. Some case cannot protect for life, such as accident case on the road, the criminal case and so on. It says that need to give some information to them that is never emancipate from the criminal case and never find bolt-hold. This system can support like case, because system processes under the security surveillance camera network and use all video files from that camera network. These videos are extracted as frames based on time and relevant frames are stored as frame sequence. The system extracts key information frames from that frames sequence with relevant time. The system handles all important key information frames and extract important object using colour features base and collects the path of that object by tracking of different background region. To track selected object, the system collects all key information frames from videos in a network with time base. The selected importance key object is searched other information key frames. To search selected object from other key frames, the system use object segmentation on colour features.
The user needs to select tracking objects from key frames a video. That selected important object is extracted feature values based on RGB features and HSV hue value. This research tests on private dataset, surveillance camera network, from Myanmar Institute of Information Technology University (MIIT), Mandalay, Myanmar. All surveillance cameras are configured at the different stable places and camera view is stable in vision. That camera network has 85 cameras totally and used HIKVISION network bullet camera and HIKVISION E series Network Speed Dome camera. This research is ongoing stage and five members are working as a group. -
An Algebraic Geometric Imaging Approach for Automatic Dairy Cow Body Condition Scoring System International conference
Thi Thi Zin, Pyke Tin, I. Kobayashi, and Y. Horii
2019 International Conference on Precision Dairy Farming Technologies and Applications (Tokyo, Japan) World Academy of Science, Engineering and Technology
Event date： 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Tokyo, Japan
In order to confirm the validity of proposed method, a monitoring video camera is set up at the milk rotary parlor to take top view images of cows. The proposed method extracts the key anatomical points and the corresponding feature vectors for each individual cows. Then the multiple regression calculator and Markov Chain Classification process are utilized to produce the estimated body condition score for each cow. The experimental results tested on 100 dairy cows from self-collected dataset and public bench mark dataset show very promising with accuracy of 98%.
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Multivariate Stochastic Analyzer for Dairy Cow Body Condition Scoring International conference
Thi Thi Zin, K. Sumi, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In this paper, we introduce a conceptual multivariate stochastic analyzer for assessing body condition scores of individual dairy cows. Specifically, by using digital image technologies and statistical stochastic methods, dairy cow body condition scoring machine is to be established. In modern precision dairy farming, the body condition score (BCS) plays an important role as an indicator for measuring health and wealth of a dairy farm. Based on the BCS, today dairy farm manage systems are improved in in various aspects such as milk production, right time for artificial insemination, prediction calving time and so on. Traditionally, human experts perform visual examinations on the key areas of cow body parts such as hook, pin bones, tail head, short ribs, and backbone starches for scoring. However, well-trained human experts become less and dairy farm sizes are bigger as a consequence manual body condition scoring is almost impractical. Thus, in this paper we propose an image technology based stochastic analyzer for automatic scoring the BCS measures of dairy cows. In order to do so, the proposed analyzer first extracts some key anatomical points of a cow by using two-dimensional images taken from top views. Then, the system will derive some distance and angular features of the anatomical points and employs stochastic sampling techniques for refining the extracted features to produce parameters of multiple regressive prediction models and to assess the body condition scores of all dairy cows in the farm. Finally, to confirm the validity of proposed analyzer, we perform some experiments by a well-known benchmark dataset. The experimental results seem to be promising with an impact of high accuracy.
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Incorporating Digital Imaging in Dairy Cow Anatomical Feature Detection International conference
Thi Thi Zin, Cho Nilar Phyo, Pyke Tin
International Conference on Digital Image and Signal Processing (DISP 2019) (Oxford University, UK)
Event date： 2019.4.29 - 2019.4.30
Language：English Presentation type：Oral presentation (general)
Venue：Oxford University, UK
In today precision dairy farming, the most commonly used technologies include wearable devices which must be attached to cows in one way or another in order to monitor cow’s behaviors. Since the wearable sensors placements may be broken or lost and can burden additional stress to the cows, it is necessary to consider an alternative and effective non-contact monitoring system. For this purpose, digital imaging technologies are suitable due to their capabilities of continuous operation and able to full automation. Thus, in this paper, we propose a digital imaging approach based on topological persistence concepts to precision dairy cow monitoring system focused on automated dairy cow anatomical feature detection. Anatomically these features define as hips, hooks, pin bones, tail-heads and rear regions of the cow body. These features will be utilized in the decision making process if and where a cow is present in an image or video frame. Once the system detects a cow in the image, the system automatically identifies an individual cow. The proposed cow anatomical feature detection and cow identification have the potentials in detecting cow body conditions, health conditions in time, milk production trends and predicting calving time and heat occurrence. Finally, by using videos taken in a real-life cow farm, the experimental results confirm the validity of proposed method.
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Dairy Cow Body Conditions Scoring System Based on Image Geometric Properties International conference
Thi Thi Zin, Pyke Tin, Ikuo Kobayashi
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In modernized precision dairy farming, the importance of dairy cow body condition scores is well recognized for making the healthy, wealthy and optimizing milk production. Although a burst amount of researches have been investigated the condition scoring problems from various aspects, not much satisfactory results have been come out yet. So, this paper will propose a geometric imaging approach for an automatic dairy cow body conditions scoring system. Specifically, some significant land marks or anatomical points are to be extracted from the top view image of a cow and their geometrical properties such as angles, length and area are investigated to estimate body condition scores. In doing so, the proposed method will employ techniques of polynomial regression, multiple regression, Markov Chain classification. Finally, some experimental results will be presented by using self-collected datasets and some well-known public datasets. The performance of preliminary results shows promising so that the approach of proposed method can lead to be applicable in real life environments.
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OCR Perspectives in Mobile Teaching and Learning for Early School Years in Basic Education International conference
Thi Thi Zin, Swe Zar Maw, Pyke Tin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
In these days, teaching and learning systems in schools with the use of mobile or portable devices such as tablets, e-readers, smartphones are becoming keen interests of educators as well as parents and teachers in worldwide. In this aspect, the early years of school children in basic education are the most challenging and important in developing effective and quality education for life. Since they are quite young and unable to dedicate time the need for easy to use and effective learning aids has become vital. Especially their writing skills are somehow needed to be improved with encouragements. In order to do so, the handwritten of characters and numerals performed by the children especially those living in less developing countries should be correctly recognized so that means and ways for remedies and solutions for improvements could be found. Thus the optical character recognition techniques for handwritten alphabets and numerals are moving into front especially the handwritten of children of early years in schools. In this paper, we introduce a Mobile Tutor - an effective and correct way of character segmentation and recognition of messy and unclear handwritten characters to help children learn and practice handwriting and early numeric operations such as addition and subtraction as well as help teachers monitor and review children’s progress. Some experiments are performed by providing tablets to the users and collecting handwritten characters from the users for recognition and analysis.
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A Study on Detection of Precursor Behaviors of Estrus in Cattle Using Video Camera International conference
Hiromitsu Hama, Tetsuya Hirata, Tsubasa Mizobuchi, Thi Thi Zin
The 2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech 2019) ( Senri Life Science Center (Osaka, Japan)) IEEE Life Sciences Technical Community
Event date： 2019.3.12 - 2019.3.14
Language：English Presentation type：Oral presentation (general)
Venue： Senri Life Science Center (Osaka, Japan)
Development of an estrus detection system by non-contact and non-invasive methods to improve productivity is a strong desire from livestock farmers with aging society. As one of the elemental technologies, we will focus on detecting precursor behaviors of estrus in cattle using video camera. First, we converted from two-dimensional motion on video image to three dimensional one. Next, some features which are well-known as estrus precursor behaviors, were selected, for example, walking speed, trajectory and relative positional relationship of two cattle. Through experimental results, we could confirm the effectiveness of our proposed algorism. As the result, although it is a small case, it was able to detect without any false positive and false negative.
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Innovations of Digital Imaging in Smart Dairy Farming Invited International conference
Thi Thi Zin
The 17th International Conference on Computer Applications (ICCA 2019) and The 11th International Conference on Future Computer and Communication (ICFCC 2019) (Novotel Hotel, Yangon, Myanmar) University of Computer Studies, Yangon
Event date： 2019.2.27 - 2019.3.1
Language：English Presentation type：Oral presentation (invited, special)
Venue：Novotel Hotel, Yangon, Myanmar
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A Hybrid Rolling Skew Histogram-Neural Network Approach to Dairy Cow Identification System International conference
Cho Nilar Phyo, Thi Thi Zin, H. Hama, I. Kobayashi
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
In this paper, we propose a hybrid method in which rolling skew histogram and neural network techniques are fused to recognize patterns and identify cows in the milking rotary parlor of dairy farms. Individual cow identification is very important for managing the welfare and health care of an individual cow and developing the body condition scoring system. Although there has some sensor-based cows' identification system, those systems require to attach the sensor devices on each cow which is costly and burden on the cows. Since the proposed method applies a single video camera which is a non-contact device for the identification of many different cow patterns, the proposed system is low cost and no burdens on the cow. In particular, the operation of the system takes place while the cows are in the milking process in rotary milking parlor where the monitoring of individual cow is more effective than some other time and places. The identification process is based on the black and white pattern on the cow's body while moving on the rotary milking parlor. For the detecting and cropping of cows' body region is carried out by using rolling the skew histogram and used for the training process of the deep convolutional neural network. The trained network is employed for the identification of individual cow in the testing process. The experiments are performed on the self-collected cow video dataset which includes around 60 different cow's body patterns that have been taken at the large-scale farm in Oita Prefecture, Japan. The experimental results show that the proposed system is promising with the overall accuracy of 96.3 % and it is very effective and practical for the real-time cow identification system needed for establishing a modern precision dairy farming.
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Framework of Cow Calving Monitoring System Using a Single Depth Camera International conference
K. Sumi, Thi Thi Zin, I. Kobayashi, Y. Horii
International Conference Image and Vision Computing New Zealand (IVCNZ 2018) (Auckland, New Zealand) IEEE Advancing Technology for Humanity (Technically co-sponsor)
Event date： 2018.11.19 - 2018.11.21
Language：English Presentation type：Poster presentation
Venue：Auckland, New Zealand
Calving difficulty is the primary cause of the problem of increasing death loss in cow-calf. It also profoundly effects on the economic impact of farmers and producers because of calves' death, injury to cows and high veterinary cost. To help the calving difficult of cows in time, long time continuous monitoring is required for deciding when and how to assist the calving process of cows. On the other hand, the continuous monitoring of cows' welfare become the major burden task for labors especially in a large farm where has a large number of cows. Therefore, the demands of sophisticated technology for automatic monitoring of cows' welfare is more and more increasing every year. In recent years, some researcher develops the automatics monitoring and predicting the cows' calving behavior by using the sensors devices such as temperature sensors and acceleration sensors. However, the sensors based system has various problems such as spalling and malfunction of the sensors and even can cause the burden on the cow because sensors are needed to put inside or on the body of the cow. To overcome those problems, in this paper, we propose an automatic detection of cows' calving behavior by using the depth camera (3D camera) along with image processing and computer vision technology and coordinate system transformation concept. The proposed system by using 3D camera can reduce the burden of both labors and cows.
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An Image Technology Approach to Dairy Cow Monitoring System Invited International conference
Thi Thi Zin
National Symposium on Livestock Research and Development 2018, The Faculty of Animal Science, Universitas Gadjah Mada (Universitas Gadjah Mada, Yogyakarta, Indonesia) The Faculty of Animal Science, Universitas Gadjah Mada
Event date： 2018.11.5
Language：English Presentation type：Oral presentation (invited, special)
Venue：Universitas Gadjah Mada, Yogyakarta, Indonesia
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ICTを活用した牛のモニタリングシステムの開発に関する研究 Invited
Thi Thi Zin, 小林 郁雄、椎屋 和久、PYKE TIN、堀井 洋一郎、濱 裕光
九州ＩＣＴイノベーションセミナー2018 (アクロス福岡) 総務省九州総合通信局、（一社）九州テレコム振興センター（KIAI）
Event date： 2018.11.2
Language：Japanese Presentation type：Public lecture, seminar, tutorial, course, or other speech
Venue：アクロス福岡