7308227
IBM Research TREC 2002 Video Retrieval System
In this paper, we describe the IBM Research system for analysis, indexing, and retrieval of video, which was applied to the TREC-2002 video retrieval benchmark. The system explores methods for fully-automatic content analysis, shot boundary detection, multi-modal feature extraction, statistical modeling for semantic concept detection, and speech recognition and indexing. The system supports querying based on automatically extracted features, models, and speech information. Additional interactive methods for querying include multiple-example and relevance feedback searching, cluster, concept, and storyboard browsing, and iterative fusion based on user-selected aggregation and combination functions. The system was applied to all four of the tasks of the video retrieval benchmark including shot boundary detection, concept detection, concept exchange, and search. In this paper, we describe the approaches for each of the tasks and discuss some of the results.
15943562
Content-based transcoding of images in the Internet
We present a system for transcoding images in the Internet in order to improve their delivery to client devices with a wide range of communication, processing, storage and display capabilities. The content-based image transcoder analyzes the images in order to classify them into image type and image purpose classes. The system then utilizes transcoding policies based on the content classes to manipulate and transcode the images. We describe the image transcoding process for a variety of client devices, including PDAs, hand-held computers (HHCs), TV browsers and color PCs, and demonstrate improvements in delivery speed and accessibility of the images in the Internet.
2339969
Interactive search fusion methods for video database retrieval
In this paper, we investigate a new method for video database retrieval using interactive search fusion. Recent video analysis techniques have enabled the extraction of a variety of descriptors of features, concepts, clusters, classification results, speech and textual terms, MPEG-7 metadata, and so on. However, given an information need users are faced with a daunting task of trying to formulate queries over these multiple disparate data sources in order to retrieve the desired video content. In this paper, we explore a novel approach based on search fusion in which the user interactively builds a query by sequentially choosing among the descriptors and data sources and by selecting from various combining and score aggregation functions to fuse results of individual searches. For example, the system allows building of queries such as "retrieve video clips that have color of beach scenes, the detection of sky, and detection of water". In this paper we present the search fusion method and evaluate the performance on a large video database.
1805433
MPEG-7 MDS Content Description Tools and Applications
In this paper, we present the tools specified by the MDS part of the MPEG-7 standard for describing multimedia data such as images and video. In particular, we focus on the description tools that represent the structure and semantics of multimedia data to whose development we have actively contributed. We also describe some of our research prototype systems dealing with the extraction and application of MPEG-7 structural and semantic descriptions. These systems are AMOS, a video object segmentation and retrieval system, and IMKA, an intelligent multimedia knowledge application using the MediaNet knowledge representation framework.
30741426
Multimedia database management systems
Introduction. Multimedia Data Types and Formats. Multimedia Database Design Issues. Text Document Indexing and Retrieval. Indexing and Retrieval of Audio. Image Indexing and Retrieval. Video Indexing and Retrieval. Integrated Multimedia Indexing and Retrieval. Techniques and Data Structures for Efficient Multimedia Similarity Search. System Support for Distributed Multimedia Databases. Measurement of Multimedia Information Retrieval Effectiveness. Products, Applications, and New Developments.
20964781
Special Issue on Image Understanding for Digital Photographs
13961662
Improving Nearest Neighbor Classifier Using Tabu Search and Ensemble Distance Metrics
The nearest-neighbor (NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good results with this technique is the choice of distance function, and correspondingly which features to consider when computing distances between samples. In this paper, a new ensemble technique is proposed to improve the performance of NN classifier. The proposed approach combines multiple NN classifiers, where each classifier uses a different distance function and potentially a different set of features (feature vector). These feature vectors are determined for each distance metric using Simple Voting Scheme incorporated in Tabu Search (TS). The proposed ensemble classifier with different distance metrics and different feature vectors (TS-DF/NN) is evaluated using various benchmark data sets from UCI Machine Learning Repository. Results have indicated a significant increase in the performance when compared with various well-known classifiers. Furthermore, the proposed ensemble method is also compared with ensemble classifier using different distance metrics but with same feature vector (with or without Feature Selection (FS)).
29643487
Stochastic network evacuation models
Abstract Stochastic network evacuation models are crucial for the safe evacuation of occupants from buildings. In this paper, we compare an analytical closed queueing network and a simulation model for analyzing the evacuation of occupants from a hospital. Evacuation times, arc congestion, and optimization of the evacuation routes and staff assigned to the evacuation network are included.
16792950
Task-structure analysis for knowledge modeling
n recent years there has been increasing interest in describing complicated information processing systems in terms of the knowledge they have, rather than by the details of their implementation. This requires a means of modeling the knowledge in a system. Several different approaches to knowledge modeling have been developed by researchers working in Artificial Intelligence (AI). Most of these approaches share the view that knowledge must be modeled with respect to a goal or task. In this article , we outline our modeling approach in terms of the notion of a task-structure, which recursively links a task to alternative methods and to their subtasks. Our emphasis is on the notion of modeling domain knowledge using tasks and methods as mediating concepts. We begin by tracing the development of a number of different knowledge-modeling approaches. These approaches share many features, but their differences make it difficult to compare systems that have been modeled using different approaches. We present these approaches and describe their similarities and differences. We then give a detailed description , based on the task structure, of our knowledge-modeling approach and illustrate it with task structures for diagnosis and design. Finally, we show how the task structure can be used to compare and unify the other approaches. A knowledge-based system (KBS) has explicit representations of knowledge as well as inference processes that operate on these representations to achieve a goal. An inference process consists of a number of inference steps, each step creating additional knowledge. The process of applying inference steps is repeated until the information needed to fulfill the requirements of the problem-solving goal or task is generated. Typically, both domain knowledge and possible inference steps have to be modeled and represented in some form. In one sense, knowledge is of general utility-the same piece can be utilized in different contexts and problems; so, unlike traditional procedural approaches, knowledge should not be tied to one task or goal. On the other hand, it is difficult to know what knowledge to put in a system without having an idea of the tasks the KBS will confront. In spite of claims of generality, all KBSs are designed with some task or class of tasks in mind. Similarly, they are designed to be operational across some range of domains. Thus, a clear understanding of the relationship between tasks, knowledge and inferences required to perform the task is needed before knowledge in …
42617820
The Optimal Deployment of Filters to Limit Forged Address Attacks in Communication Networks
We consider forged address attacks in communication networks, wherein an attacking node forges the address of communication requests sent to a victim node. Unless the victim can ascertain the origin of the attack, it must cease to respond to communication requests until the attack subsides. We examine the problem of identifying a minimum cardinality subset of nodes on a network, such that placing route-based filters on these nodes provides a prescribed level of security. We model the problem as an integer program and illustrate its performance on randomly generated networks. Next, we develop a greedy heuristic to deploy filters in these networks, and compare its solution quality to that of the integer programming approach. These findings are then used to motivate both the importance of addressing this problem by optimal techniques and to motivate future research approaches for solving such problems.
2547072
An orthogonal taxonomy for hyperlink anchor generation in video streams using OvalTine
As dynamically linked content follows the progression of statically linked media into the realm of video, new opportunities for link creation become apparent. In this paper we describe a real-time video hypermedia system with user-definable linkage areas, in a distributed collaborative environment. We also investigate the extension of such a system to automated link creation in video streams. In the process, we identify and describe orthogonal issues of hypervideo anchor creation. An example system, OvalTine, has been produced to illustrate several potential uses through configuration of an extended video conferencing application on the SGI O2 platform.