9196724
STRG-Index: spatio-temporal region graph indexing for large video databases
In this paper, we propose new graph-based data structure and indexing to organize and retrieve video data. Several researches have shown that a graph can be a better candidate for modeling semantically rich and complicated multimedia data. However, there are few methods that consider the temporal feature of video data, which is a distinguishable and representative characteristic when compared with other multimedia (i.e., images). In order to consider the temporal feature effectively and efficiently, we propose a new graph-based data structure 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 in which redundant subgraphs are eliminated to reduce the index size and search time, because the computational complexity of graph matching (subgraph isomorphism) is NP-complete. In addition, a new distance measure, called Extended Graph Edit Distance (EGED), is introduced in both non-metric and metric spaces for matching and indexing respectively. Based on STRG and EGED, we propose a new indexing method STRG-Index, which is faster and more accurate since it uses tree structure and clustering algorithm. 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 for various query loads in terms of cost and speed.
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.
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.
13494624
Security policies
A security policy is a high-level specification of the security properties that a given system should possess. It is a means for designers, domain experts and implementers to communicate with each other, and a blueprint that drives a project from design through implementation and validation. We offer a survey of the most significant security policy models in the literature, showing how “security” may mean very different things in different contexts, and we review some of the mechanisms typically used to implement a given security policy.
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.
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
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.
14238943
Secure query processing against encrypted XML data using Query-Aware Decryption
Dissemination of XML data on the internet could breach the privacy of data providers unless access to the disseminated XML data is carefully controlled. Recently, the methods using encryption have been proposed for such access control. However, in these methods, the performance of processing queries has not been addressed. A query processor cannot identify the contents of encrypted XML data unless the data are decrypted. This limitation incurs overhead of decrypting the parts of the XML data that would not contribute to the query result. In this paper, we propose the notion of Query-Aware Decryption for efficient processing of queries against encrypted XML data. Query-Aware Decryption allows us to decrypt only those parts that would contribute to the query result. For this purpose, we disseminate an encrypted XML index along with the encrypted XML data. This index, when decrypted, informs us where the query results are located in the encrypted XML data, thus preventing unnecessary decryption for other parts of the data. Since the size of this index is much smaller than that of the encrypted XML data, the cost of decrypting this index is negligible compared with that for unnecessary decryption of the data itself. The experimental results show that our method improves the performance of query processing by up to six times compared with those of existing methods. Finally, we formally prove that dissemination of the encrypted XML index does not compromise security.
13362734
FINDIT: a fast and intelligent subspace clustering algorithm using dimension voting
Abstract The aim of this paper is to present a novel subspace clustering method named FINDIT. Clustering is the process of finding interesting patterns residing in the dataset by grouping similar data objects from dissimilar ones based on their dimensional values. Subspace clustering is a new area of clustering which achieves the clustering goal in high dimension by allowing clusters to be formed with their own correlated dimensions. In subspace clustering, selecting correct dimensions is very important because the distance between points is easily changed according to the selected dimensions. However, to select dimensions correctly is difficult, because data grouping and dimension selecting should be performed simultaneously. FINDIT determines the correlated dimensions for each cluster based on two key ideas: dimension-oriented distance measure which fully utilizes dimensional difference information, and dimension voting policy which determines important dimensions in a probabilistic way based on V nearest neighbors' information. Through various experiments on synthetic data, FINDIT is shown to be very successful in the high dimensional clustering problem. FINDIT satisfies most requirements for good clustering methods such as accuracy of results, robustness to the noise and the cluster density, and scalability to the dataset size and the dimensionality. Moreover, it is gracefully scalable to full dimension without any modification to algorithm.
207081381
Enumeration of Regular Graph Coverings Having Finite Abelian Covering Transformation Groups
Several isomorphism classes of graph coverings of a graph G have been enumerated by many authors. An enumeration of the isomorphism classes of n-fold coverings of a graph G was done by Kwak and Lee [Canad. J. Math., XLII (1990), pp. 747--761] and independently by Hofmeister [Discrete Math., 98 (1991), pp. 437--444]. An enumeration of the isomorphism classes of connected n-fold coverings of a graph G was recently done by Kwak and Lee [J. Graph Theory, 23 (1996), pp. 105--109]. But the enumeration of the isomorphism classes of regular coverings of a graph G has been done for only a few cases. In fact, the isomorphism classes of ${\cal A}$-coverings of G were enumerated when ${\cal A}$ is the cyclic group $\BZ_n$, the dihedral group $\BD_n$ (n: odd), and the direct sum of $m$ copies of $\BZ_p$. (See [Discrete Math., 143 (1995), pp. 87--97], [J. Graph Theory, 15 (1993), pp. 621--627], and [Discrete Math., 148 (1996), pp. 85--105]). 
In this paper, we discuss a method to enumerate the isomorphism classes of connected ${\cal A}$-coverings of a graph G for any finite group ${\cal A}$ and derive some formulas for enumerating the isomorphism classes of regular n-fold coverings for any natural number n. In particular, we calculate the number of the isomorphism classes of ${\cal A}$-coverings of G when ${\cal A}$ is a finite abelian group or the dihedral group $\BD_n$. Our method gives partial answers to the open problems 1 and 2 in [Discrete Math., 148 (1996), pp. 85--105] and also gives a formula to calculate the number of the subgroups of a given index of any finitely generated free abelian group.
9722973
Monitoring Data Archives for Grid Environments
Developers and users of high-performance distributed systems often observe performance problems such as unexpectedly low throughput or high latency. To determine the source of these performance problems, detailed end-to-end monitoring data from applications, networks, operating systems, and hardware must be correlated across time and space. Researchers need to be able to view and compare this very detailed monitoring data from a variety of angles. To address this problem, we propose a relational monitoring data archive that is designed to efficiently handle high-volume streams of monitoring data. In this paper we present an instrumentation and monitoring event archive service that can be used to collect and aggregate detailed end-to-end monitoring information from distributed applications. This archive service is designed to be scalable and fault tolerant. We also show how the archive is based on the "Grid Monitoring Architecture" defined by the Global Grid Forum.