11550445
Multimedia Data Mining Framework for Raw Video Sequences
In this paper, we propose a general framework for real time video data mining to be applied to the raw videos (traffic videos, surveillance videos, etc.). We investigate whether the existing techniques would be applicable to this type of videos. Then, we introduce new techniques which are essential to process them in real time. The first step of our frame work for mining raw video data is grouping input frames to a set of basic units which are relevant to the structure of the video. We call this unit as segment. This is one of the most important tasks since it is the step to construct the building blocks for video database and video data mining. The second step is characterizing each segment to cluster into similar groups, to discover unknown knowledge, and to detect interesting patterns. To do this, we extract some features (motion, object, colors, etc.) from each segment. In our framework, we focus on motion as a feature, and study how to compute and represent it for further processes. The third step of our framework is to cluster the decomposed segments into similar groups. In our clustering, we employ a multi-level hierarchical clustering approach to group segments using category and motion. Our preliminary experimental studies indicate that the proposed framework is promising.
223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed method.
16719880
Jikzi - a new framework for security policy, trusted publishing and electronic commerce
In this paper, we will describe a thread of research, which we have followed off and on at Cambridge for about three years. Our topic is the security of electronic documents, in the broad sense: how can we be sure of the authenticity of things that are published electronically? This started off as a relatively small project, which we thought would take only a few weeks. The goal was to help our medical informatics department publish information such as drug formularies and treatment protocols on the hospital LAN or PC diskettes, in an appropriately dependable way. It rapidly became clear that the problem was much larger and more complex; a general solution would not only cope with 'content' - text, audio, video, software, whatever - but also with objects such as public key certificates. If done properly, it would give us a systematic way to deal with security policy on the web. Our goal now is to let people build integrated publishing and e-commerce services using simple, uniform and appropriate mechanisms. Our proposed solution is a single transparent markup language that allows us to support multiple security policies, plus supporting material ranging from a test implementation to an authentication logic.
17811625
A Graph-Based Approach for Modeling and Indexing Video Data
In this work, we propose new graph-based data model and indexing to organize and manage video data. To consider spatial and temporal characteristics of video, we introduce a new graph-based data model called spatio-temporal region graph (STRG). Unlike existing graph-based data structures which provide only spatial features, the proposed STRG further provides temporal features, which represent temporal relationships among spatial objects. The STRG is decomposed into its subgraphs object graphs (OGs) and background graphs (BGs). In addition, a new distance measure, called extended graph edit distance (EGED), is introduced in metric space for matching and indexing. Based on clustering and EGED, we propose a new indexing method STRG-index, which is faster and more accurate. We compare the STRG-Index with the M-tree, which is a popular tree-based indexing method for multimedia data. The STRG-index outperforms the M-tree in terms of cost and speed
26803013
Jikzi: A New Framework for Secure Publishing
We present a new way to deal with security policy on the web. Our aim is to let people build integrated publishing and e-commerce services using appropriate, simple and uniform mechanisms. Our goal is a single framework that applies equally to the publication of catalogues, music, software, public key certificates and even old fashioned books. Our prototype framework, Jikzi, supports multiple security policies – even in the same document – with a single transparent markup language.
12522566
Real Time Video Data Mining for Surveillance Video Streams
We extend our previous work [1] of the general framework for video data mining to further address the issue such as how to mine video data using motions in video streams. To extract and characterize these motions, we use an accumulation of quantized pixel differences among all frames in a video segment. As a result, the accumulated motions of segment are represented as a two dimensional matrix. Further, we develop how to capture the location of motions occurring in a segment using the same matrix generated for the calculation of the amount. We study how to cluster those segmented pieces using the features (the amount and the location of motions) we extract by the matrix above. We investigate an algorithm to find whether a segment has normal or abnormal events by clustering and modeling normal events, which occur mostly. In addition to deciding normal or abnormal, the algorithm computes Degree of Abnormality of a segment, which represents to what extent a segment is distant to the existing segments in relation with normal events. Our experimental studies indicate that the proposed techniques are promising.
30195525
Nondefinite vs. Definite Causal Theories
Nonmonotonic causal logic can be used to represent properties of actions, including actions with conditional and indirect effects, nondeterministic actions, and concurrently executed actions. The definite fragment of causal logic can be mapped to propositional logic by the process of completion, and this idea has led to the development of the Causal Calculator. In this note, we show how to turn arbitrary causal theories into definite theories without changing the sets of models. The translation consists of two parts: one is a set of definite rules which is obtained from the given theory by translating each rule one by one, in a modular way, and the other is a set of constraints similar to loop formulas for logic programs. Our result characterizes the semantics of causal logic in terms of propositional logic and tells us that an essential difference between the semantics of causal logic and the answer set semantics is related to the definition of a loop in each.
376779
Interactive control of avatars animated with human motion data
Real-time control of three-dimensional avatars is an important problem in the context of computer games and virtual environments. Avatar animation and control is difficult, however, because a large repertoire of avatar behaviors must be made available, and the user must be able to select from this set of behaviors, possibly with a low-dimensional input device. One appealing approach to obtaining a rich set of avatar behaviors is to collect an extended, unlabeled sequence of motion data appropriate to the application. In this paper, we show that such a motion database can be preprocessed for flexibility in behavior and efficient search and exploited for real-time avatar control. Flexibility is created by identifying plausible transitions between motion segments, and efficient search through the resulting graph structure is obtained through clustering. Three interface techniques are demonstrated for controlling avatar motion using this data structure: the user selects from a set of available choices, sketches a path through an environment, or acts out a desired motion in front of a video camera. We demonstrate the flexibility of the approach through four different applications and compare the avatar motion to directly recorded human motion.
18004950
Trajectory clustering: a partition-and-group framework
Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.
11135972
Challenges in Cross-Cultural/Multilingual Music Information Seeking
Understanding and meeting the needs of a broad range of music users across different cultures and languages are central in designing a global music digital library. This exploratory study examines cross-cultural/multilingual music information seeking behaviors and reveals some important characteristics of these behaviors by analyzing 107 authentic music information queries from a Korean knowledge search portal Naver 지식 (knowledge) iN and 150 queries from Google Answers website. We conclude that new sets of access points must be developed to accommodate music queries that cross cultural or language boundaries.
10486912
VTAssist: a location-based feedback notification system for the disabled
The needs of individuals with limited mobility have not been given as much importance as those of other users of internet-accessible mobile devices. Disabled users have information and service needs that are unique and a timely delivery of these services and information can be invaluable. This has motivated us toward the development of VTAssist, an application that attempts to provide critical location-based information about building accessibility to impaired users. This paper discusses our initial implementation of VTAssist and reports on preliminary evaluation results. Our results indicate that our system can help wheelchair users to better understand and navigate around environments.