Papers - THI THI ZIN
-
Manipulation-Killer web information ranking System
Tin P., Zin T., Toriu T., Hama H.
ICIC Express Letters, Part B: Applications 2 ( 3 ) 523 - 528 2011.6
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters, Part B: Applications
Link analysis has been widely used to evaluate the importance of web pages. Page-Rank, the most famous link analysis algorithm, offers an effective way to rank the pages. However, the algorithm ignores four facts. First, nowadays the way that users retrieve information is different from the previous way when web search engine was not extensively used. Second, inter-site links and intra-site links should not be treated equally. A link from a different site is more important for a page than that within the same site. Third, most users start their browsing from a homepage, which should be given more weight than other pages. Finally, most of existing ranking systems for linked networks can be manipulated by spammers who strategically place links. In this paper, we pro-pose a novel ranking system called manipulation-killer rank (MK-Rank) as a solution to these problems. Specifically, we show that expected passage time to reach a web page in a random walk measures essentially the same quantity as Page-Rank, whereas it does not depend on the manipulated in-links. We also show that it resists tampering by individuals or groups who strategically place manipulated links. In addition, we present an algorithm to efficiently compute passage time for all nodes in a massive graph; conventional algo-rithms do not scale adequately. Experimental results show that our MK-Rank algorithm outperforms other famous ranking algorithms, including Page-Rank and Traffic Rank, especially on sites recommendation and web spam avoidance. © 2011 ICIC International.
-
Fast multi-slit composition method using attitude measurement unit for pedestrian detection
Hashimoto Y., Zin T., Toriu T., Hama H.
ICIC Express Letters, Part B: Applications 2 ( 3 ) 541 - 546 2011.6
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters, Part B: Applications
During the next decade, on-board pedestrian detection systems will play a key role in the challenge of increasing traffic safety. The main goal of these systems, to detect pedestrians in urban scenarios, involves overcoming difficulties like processing outdoor scenes from a mobile platform and searching for aspect-changing objects in cluttered environments. Such systems thus combine various techniques in state-of-the-art computer vision. In this paper, we present a novel method that uses an Attitude Measurement Unit (AMU) in conjunction with a camera for tracking and which performs well in dynamic and cluttered outdoor environments as long as the target occlusions and losses are temporary. The main purpose is to demonstrate the advantages of using an AMU as a means of on-road pedestrian detection for automobiles over more conventional means. Specifically, we present a two module systems based on both 2D and 3D sensor cues. The first module uses fipitch and roll angles for calculating the vanishing line on the image to select a coherent set of regions of interest (ROIs) to be further analyzed. The second module develops a modified multi-slit method to classify the incoming ROIs into pedestrian and non-pedestrian in order to refine the final results. Our results indicate the integration of the proposed techniques gives rise to a promising system. © 2011 ICIC International.
-
Unattended object intelligent analyzer for consumer video surveillance
Zin T., Tin P., Hama H., Toriu T.
IEEE Transactions on Consumer Electronics 57 ( 2 ) 549 - 557 2011.5
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：IEEE Transactions on Consumer Electronics
Consumer video camera surveillance with the continuous advancements of image processing technologies is emerging for consumer world of applications. Technology for detecting objects left unattended in consumer world such as shopping malls, airports, railways stations has resulted in successful commercialization, worldwide sales and the winning of international awards. However, as a consumer video application the need is now greater than ever for a surveillance system that is robustly and effectively automated. In this paper, we propose an intelligent vision based analyzer for semantic analysis of objects left unattended relation with human behaviors from a monocular surveillance video, captured by a consumer camera through cluttered environments. Our analyzer employs visual cues to robustly and efficiently detect unattended objects which are usually considered as potential security breach in public safety from terrorist explosive attacks. The proposed system consists of three processing steps: (i) object extraction, involving a new background subtraction algorithm based on combination of periodic background models with shadow removal and quick lighting change adaptation,(ii) extracted objects classification as stationary or dynamic objects, and (iii) classified objects investigation by using running average about the static foreground masks to calculate a confidence score for the decision making about event (either unattended or very still person). We show attractive experimental results, highlighting the system efficiency and classification capability by using our real-time consumer video surveillance system for public safety application in big cities. © 2011 IEEE.
-
A Markov random walk model for loitering people detection
Zin T., Tin P., Toriu T., Hama H.
Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010 680 - 683 2010.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010
Today video surveillance systems are widely used in public spaces, such as train stations or airports, to enhance security. In order to observe large and complex facilities a huge amount of cameras is required. These create a massive amount of data to be analyzed. It is therefore crucial to support human security staff with automatic surveillance applications, which will create an alert if security relevant events are detected. This way video surveillance could be used to prevent potentially dangerous situations, instead of just being used as forensic instrument, to analyze an event after it happened. In this treatise we present a surveillance system which supports human operators, by automatically detecting loitering people. Usually, loitering human behavior often leads to abnormal situations, like suspected drug-dealing activity, bank robbery, and pickpocket, etc. Thus, the problem of loitering detection in image sequences involving situations with multiple objects is studied based two dimensional Markov random walks in which both motion and appearance features describing the movements of a varying number of objects as well as their entries and exits are used. To obtain efficient and compact representations we encode the spatiotemporal information of intra-inter trajectory contexts into the transition matrix of a Markov Random Walk, and then extract its stationary distribution and boundary crossing probabilities as final detection criteria. The model is also made less sensitive to uninteresting objects occluding the region of interest by integration out their effect on the observation probabilities. The resulting system is tested on the real life dataset scenarios giving 95% performance results. © 2010 IEEE.
-
A stochastic model for popularity measures in web dynamics Reviewed
H. Hama H., Pyke Tin, Thi Thi Zin, T. Toriu
Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010 676 - 679 2010.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010
In this paper, we propose a stochastic web dynamic model based on the concept of queuing theory to measure popularity of websites in the World Wide Web. We assume that the characteristics of a website such as novelty, popularity, reliability, and relevancy are governed by two major forces: internal or self-growth of each website and external functions acting on the website. In stochastic language, these two forces can be considered as random variables and able to investigate the important characteristics of websites. These characteristics include a probability distribution of the number of visitors to websites, the visiting times distribution, users' attention, the functional growth and decay of individual websites, the relationship between the dynamics of the web and its structure. We then define and investigate measuring process of popularity of websites using stochastic difference equations based on the structure of the web taken users' attention into account. For validation, we present some simulation results with the respect to parameter variations in the model. It shows that the proposed model can efficiently and adequately analyze the characteristics and behaviors of websites in web dynamical system. © 2010 IEEE.
-
Multivariate web information reliability search engine
Hama H., Tin P., Zin T., Toriu T.
ICIC Express Letters 4 ( 6 B ) 2457 - 2462 2010.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters
This paper proposes a novel multivariate analysis approach to web information reliability search systems. In this analysis, we introduce a new representation of the web as a directed stochastic hyper-graph, instead of a simple graph, where links can connect not only pairs of web pages, but also pairs of disjoint sets of pages. The stochastic hyper-graph is constructed by regrouping the set of pages into non-overlapping page-sets (subsets) and using the links between pages of distinct page-sets to create weighted hyperarcs with the goal of providing more reliable information. We then embed the hyper-graph structure into a Layered Markov Model in which transitions among web sites, page-sets and web pages are distinguished to compute reliability of web information. In addition, personalized rankings which are keys to next generation search engine will be produced by adapting the computation at local and global layers. Finally, we present some illustrative simulation results showing that the ranking system generated by the proposed approach is qualitatively comparable to or even better and more reliable than the ranking produced by some famous search engines such as Google. ICIC International (5)2010 ISSN 1881-803X.
-
HOG embedded Markov chain model for pedestrian detection
Zin T., Hama H., Tin P., Toriu T.
ICIC Express Letters 4 ( 6 B ) 2463 - 2468 2010.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters
This paper presents a new method for pedestrian detection by establishing Histograms of Oriented Gradients (HOG) embedded Markov chain model based on the cooccurrence of dominant orientations of gradients. In this model, HOG are used to obtain dominant orientations and their co-occurrences are computed by using various positional Structuring Elements (SEs). We then embed the HOG pair co-occurrences into a Markov chain. Having defined the embedded Markov chain, the corresponding joint probability density functions (pdf) are derived and used as Markov similarity features for pedestrian detection process. Due to the use of various positional SEs, the derived features can express complex shapes of objects with local and global distributions of gradient orientations. Experimental results on common datasets and comparison with some previous methods are given. The results show that the performance of our method is significantly well and it outperforms some existing methods such as conventional co-occurrence and HOGs. ICIC International © 2010 ISSN 1881-803X.
-
A novel way of computing multimedia information similarities
Zin T., Tin P., Toriu T., Hama H.
ICIC Express Letters, Part B: Applications 1 ( 1 ) 27 - 32 2010.9
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters, Part B: Applications
This paper presents a new perspective on characterizing the similarity be- tween elements in multimedia information systems concerning with images, text docu- ments or, more generally, nodes of a weighted and undirected graph. It is based on a sequence of Embedded Markov-chains and its rich properties. More precisely, we com- pute quantities such as the steady state probability distributions and the average commute time, that provide similarities between any pair of nodes or information. This approach is not limited to only images but it is applicable to any type of data such as range sensor data, communication frequency data and so on. Besides, it is adaptable for detecting and retrieving information from the multimedia database by using our newly developed Markov-based similarity measures. Specifically, the proposed system contributes a new method of foreground/background modeling in visible or non-visible multi-sensors infor- mation processing, detection, tracking and analyzing human-machine related surveillance systems. Experimental results on real life data sets show that the Markov Chain-based similarities perform well in comparison with other methods. © 2010 ICIC International.
-
A stochastic model for web reliability ranking system Reviewed
Pyke Tin, Thi Thi Zin, T. Toriu, H. Hama
ICIC Express Letters 4 ( 3 ) 705 - 711 2010.6
Language：English Publishing type：Research paper (scientific journal) Publisher：ICIC Express Letters
The World Wide Web is used, by an increasing number of people as an ever expanding source of information on almost every topic imaginable. However, useful data, is often buried, in large quantities of low-reliability content. Estimation of Web information reliability is valuable for diverse applications, such as a, search result ranking and, a, direction of crawlers. In this paper, we propose a, novel stochastic model for web information ranking system, which enables us to search useful and, reliable knowledge information. Specifically, a multiple state reliability ranking model based on the theory of Markov chain is developed, by assuming that the likelihood, of a, statement on the Web can be trusted, using standards developed, by information scientists, and, the link structure of associated, web pages. We then cluster relevant and, reliable webpages based, on whether they can be trusted, or not. Finally, the proposed model is tested, on an academic search engine and, show how the reliability ranks can be used, for searching a, useful knowledge.
-
Human behaviors analysis at or near public transportation asset
Thi Thi Zin, K. Fujimura, S. Kamijo
17th ITS World Congress 2010
Authorship：Lead author Language：English Publishing type：Research paper (scientific journal) Publisher：17th ITS World Congress
Security of human lives and property has always been a major concern for civilization for several centuries. In modern civilization, the threats of theft, accidents, terrorists' attacks and riots are ever increasing in public access areas such as airports, train stations, shopping malls, banks and etc. Due to the high amount of useful information that can be extracted from a video sequence, video surveillance has come up as an effective tool to forestall these security problems. In surveillance systems, understanding human behaviors and activities arising out of the interactions of various objects, as well as their evolution over time is an important problem. The protection of critical transportation assets and infrastructure is an important topic in these days. In this paper, we develop a new rule based approach to smart video surveillance system for detecting situations where people may be in peril, as well as suspicious action or interactions at or near critical transportation assets. For organizational purposes, the surveillance operationally-relevant behaviors are divided into three general groups: (i) single person or no interaction, (ii) multiple person interactions, and (iii) person-facility/location interactions. The behavior analysis is accomplished through the development of geometric and motion visual features for each pedestrian. With this information, the system could alert authorities if pedestrians display suspicious behaviors. The performance evaluation of the proposed system is carried out by using the video sequences taken in the real life environments of rail stations. The experimental results show the high accuracy rates.
-
Optimal crawling strategies for multimedia search engines Reviewed
H. Hama, Thi Thi Zin, Pyke Tin
IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing 182 - 185 2009.12
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing
In this paper we propose a novel optimal crawling strategy for next-generation multimedia search engines. We consider here a Web crawl as a two-dimensional (2D) random walker on a graph whose vertices are the Web pages and whose edges are the hyperlinks. The proposed crawler is a two-part scheme optimizing the crawling process in such a way that the average level of staleness over all pages is minimized and the quality of search engine from user's perspective is maximized. In doing so, we employ techniques from probability theory and the theory of functional equations which are highly computationally efficient-crucial for practicality because the size of the problem in the Web environment is immense. We show that a combination of breadth-depth crawling including the largest sites is a practical and optimal strategy. In particular, several probabilistic models for user browsing in infinite Web are proposed and studied to estimate how deep and breadth a crawler must go to download a significant portion of the Web site that is actually visited. Experimental and simulation results show that a crawler needs to download just a few levels in depth and breadth to reach the maximum number of pages that users actually visit. It also suggests that the largest sites should be included in the crawling process. © 2009 IEEE.
-
Dominant color embedded Markov chain model for object image retrieval
Zin T., Tin P., Toriu T., Hama H.
IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing 186 - 189 2009.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：IIH-MSP 2009 - 2009 5th International Conference on Intelligent Information Hiding and Multimedia Signal Processing
This paper proposes a new and compact method for object image retrieval fusing Dominant Colors (DCs) and embedded Markov chain concepts. This proposed method uses combined color-texture features which are characterized in terms of their spatial interaction or interrelationship properties, modeled by means of a set of embedded Markov chains, each associated with a major spatial direction. Specifically, DCs are extracted from the object image, which are encountered pixel-wise along a given direction to form an embedded Markov chain. Normalizing the resultant Markov chains over all specified directions, the corresponding stationary distribution is derived and served as Markov Feature-Vector (MFV). We then employ the chi square distance between the feature vectors in comparing similarity of images. The MFV involves spatial structure information of both within and between dominant color regions. Moreover, it keeps simplicity, compactness, efficiency, and robustness. We conduct experiments using a comprehensive set of images including deformable shapes. Experimental results show that the proposed method can retrieve an important number of correct images with very high accuracy while the mismatch ratio remains constant. © 2009 IEEE.
-
Bundling multislit-HOG features of near infrared images for pedestrian detection
Zin T., Tin P., Hama H.
2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009 302 - 305 2009.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
In this paper we present a novel scheme where image features are bundled into local groups. Specifically, features of Near Infrared (NIR) images extracted by using Histogram of Oriented Gradients (HOG) descriptor and those by our multislit method are bundled into a single descriptor. The method involves first localizing the spatial layout of body parts (head, torso, and legs) in individual frames using multislit structures, and associating these through a series of extracting HOG features. A bundled feature vector describing various types of poses is then constructed and used for detecting the pedestrians. Experiments with a database of NIR images show that our scheme achieves a substantial improvement in average precision over the baseline conventional HOG approach. Detection and recognition performance is less computationally expensive than existing approaches. © 2009 IEEE.
-
An optimal choice of morphological operating center for object image retrieval
Hama H., Zin T., Tin P.
2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009 298 - 301 2009.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
In this paper we introduce a novel and simple schemes to develop an optimal choice of morphological Operating Center (OC) for object image retrieval. A variation of the standard morphological operators which require the choice of an OC is discussed. The proposed method is based on combinations of statistical and dynamic programming techniques in which recursive equations on the basis of dilation by using the principle of optimality and minimizing unnecessary background area of the objects are applied. We also present the application of mathematical morphology with Structuring Elements (SEs) which are elongated in the angular direction. The experimental results show that the optimal choice of OC provides satisfying retrieval results. © 2009 IEEE.
-
Reliability based web information ranking system
Tin P., Zin T., Toriu T., Hama H.
2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009 294 - 297 2009.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
In this paper, we propose a reliability based Web information ranking system which enables searching useful and reliable knowledge information. The proposed system will contain subsystems for reliability ranking, information clustering based on reliability. The reliability ranking system will estimate the likelihood that a statement on the Web can be trusted using standards developed by information scientists, and the link structure of associated Web pages. The clustering will cluster relevant and reliable information based on whether or not they can be trusted or not. We test these models on an academic search engine and show how the reliability information ranks can be used as a useful knowledge. © 2009 IEEE.
-
A hybrid ranking of link and popularity for novel search engine Reviewed
H. Hama, Thi Thi Zin, Pyke Tin
International Journal of Innovative Computing, Information and Control 5 ( 11 ) 4041 - 4049 2009.11
Language：English Publishing type：Research paper (scientific journal) Publisher：International Journal of Innovative Computing, Information and Control
In this paper, we explore a new paradigm to enable Web search at image level reflecting the most relevant results to the users. So we introduce a new concept of Popularity-based Rank (PR), a content-level ranking and searching model for image retrieval. Specifically, we establish a PR Operation which is combined with new link structure analysis. The strategy to decide searching order by taking similarity into consideration is also proposed and proved to be effective and efficient. Experimental results show that the combined analysis can achieve significantly better ranking results than naively applying page-level ranking on the image model which is usually used in the current search engines. © 2009 ISSN.
-
Spatial image retrieval based on dynamic thresholding
Zin T., Hama H., Tin P.
International Journal of Innovative Computing, Information and Control 5 ( 11 ) 4051 - 4059 2009.11
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：International Journal of Innovative Computing, Information and Control
In this paper, we present a spatial image retrieval method based on dynamic thresholding. The proposed method can retrieve spatial image patterns with high accuracy and speed from images with complicated backgrounds. For simplicity, we consider the query images as specified rectangular-shaped or circular-shaped framed images. First, by introducing a dynamic thresholding system, the images can be partitioned into Peak Color Regions (PCRs). Consequently, the proposed method requires low computational complexity giving optimal feasible results for detection and segmentation. Due to compact representation and low complexity of color features, direct histogram comparison is to be used for extraction of PCRs. Since the number of the PCRs is much smaller than that of the image pixels, the proposed method allows a low dimensional image processing. The effectiveness of the proposed method is confirmed through experiments with various images. © 2009 ISSN.
-
Zin T., Takahashi H., Hama H.
International Journal of Innovative Computing, Information and Control 5 ( 3 ) 751 - 761 2009.3
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：International Journal of Innovative Computing, Information and Control
Nowadays, person detection in far infrared (FIR) images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes. Since the properties of FIR images different from visible images, it is not known what kind of scheme is appropriate for person detection in FIR images. In this paper, we propose two novel methods for person detection using FIR images: (i) body parts detection method and (ii) Gravity Center (GC) movement pattern method. First, we introduce the multi-slit method along with vanishing line for extraction of head regions. After the head region is detected and segmented, the person body and legs regions are roughly estimated by size ratios. The histograms of Sobel edge of such estimated regions are used to confirm the segmented head. This method can be applicable to person detection at both near and far distances in indoor and outdoor scenes. Second, we propose a sequential decision method by investigating GC movement patterns. It is very simple and especially valid for images at near distances. Our experiments demonstrate the effectiveness of the proposed methods and the advantages in dealing with person detection. Finally, comparative study and further extendable potential applications of the proposed methods are pointed out to be focused in our future research. © 2009 ISSN.
-
Ranking system for image database using special type of markov chain
Hama H.
Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008 556 - 563 2008.12
Language：English Publishing type：Research paper (scientific journal) Publisher：Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008
In this paper, we explore and examine a new novel approach to image ranking systems based on some special types of Markov chain along with new concepts of popularity and relevancy measures for image database. To be specific, this approach introduces a family of special Markov chain models in which serial correlations are explicitly involved so that we can use them as correlations among the images. By using these models, we develop a ranking function for the image database. On the other hand, 'popularity' and 'relevancy' concepts are introduced and used for developing an alternative ranking function for the database. In the process of developing ranking functions we use a method of queue-based stochastic difference equations. We then blend two ranking functions, to propose a new ranking system for searching order of image database. Since the proposed ranking system considers concepts of correlations, popularity and relevancy altogether, it is beneficial to a modern search engine for investigating behavior and effects of those parameters on the search results. Some illustrative examples and simulation results are presented with reference to a real world application domain. © 2008 IEEE.
-
Zin T., Hama H., Tin P.
Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008 548 - 555 2008.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Proceedings - Digital Image Computing: Techniques and Applications, DICTA 2008
This paper proposes a new method for object retrieval in image and video databases. The proposed system uses the histogram based approach along with Angular Radial Representation (ARR). In addition, concepts of Dominant Colors (DCs) and morphological dilation using ring-shaped and fanshaped Structuring Elements (SEs) are also applied. It is found that the approach is not only invariant to rotation, translation and scaling but also valid for low resolution images and partial occlusion. The retrieval effectiveness of the proposed system is shown through experiments using a comprehensive set of images including deformable shapes. © 2008 IEEE.