1648265
Tools and techniques for color image retrieval
The growth of digital image and video archives is increasing the need for tools that effectively filter and efficiently search through large amounts of visual data. Towards this goal we propose a technique by which the color content of images and videos is automatically extracted to form a class of meta-data that is easily indexed. The color indexing algorithm uses the back- projection of binary color sets to extract color regions from images. This technique provides for both the automated extraction of regions and representation of their color content. It overcomes some of the problems with color histogram techniques such as high-dimensional feature vectors, spatial localization, indexing and distance computation. We present the binary color set back-projection technique and discuss its implementation in the VisualSEEk content- based image/video retrieval system for the World Wide Web. We also evaluate the retrieval effectiveness of the color set back-projection method and compare its performance to other color image retrieval methods.
20964781
Special Issue on Image Understanding for Digital Photographs
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.
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.
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.
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.
33249562
The Transfusion Medicine Tutor: Using Expert Systems Technology to Teach Domain-Specific Problem-Solving Skills
This study provides data regarding the effectiveness of the expert system-based Transfusion Medicine Tutor (TMT) when used by medical technology students to learn an important problem-solving task, the identification of alloantibodies in a patient's blood for the purpose of finding compatible blood for transfusion. The results show that the students who were taught by an instructor using TMT to provide the instructional environment went from 0% correct on a pre-test case to 87%–93% correct on post-tests (N=15). This compares with an improvement rate of 20% by a control group (N=15) who used a passive version of the system with the tutoring functions turned off. The results also demonstrate the importance of relying on objective performance data rather than questionnaire data to evaluate systems, as there was no difference in the subjective responses of the students to these two different versions of the system.
18179112
Balancing performance and flexibility with hardware support for network architectures
The goals of performance and flexibility are often at odds in the design of network systems. The tension is common enough to justify an architectural solution, rather than a set of context-specific solutions. The Programmable Protocol Processing Pipeline (P4) design uses programmable hardware to selectively accelerate protocol processing functions. A set of field-programmable gate arrays (FPGAs) and an associated library of network processing modules implemented in hardware are augmented with software support for function selection and composition, and applied to processing-intensive portions of a user-programmable protocol stack. The system is sufficiently flexible to support protocol stacks that are dynamically altered in reaction to changing network conditions or user needs.The P4 can be transparently inserted into a conventional protocol architecture, such as that of TCP/IP. This experimental demonstration shows that the P4's programmability can be used to significantly improve the performance of TCP/IP under operating conditions where the protocol would perform poorly without augmentation. Generalizing from these experiments, the P4 is shown to have many applications as an open platform for implementing adaptive and programmable networks, and has illustrated new security issues that arise in FPGA-based architectures.The P4 and closely-related systems, such as network processors, are attractive architectural solutions to balancing performance and flexibility.
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)).
7794743
Efficient, automatic web resource harvesting
There are two problems associated with conventional web crawling techniques: a crawler cannot know if all resources at a non-trivial web site have been discovered and crawled ("the counting problem") and the human-readable format of the resources are not always suitable for machine processing ("the representation problem"). We introduce an approach that solves these two problems by implementing support for both the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) and MPEG-21 Digital Item Declaration Language (DIDL) into the web server itself. We present the Apache module "mod_oai", which can be used to address the counting problem by listing all valid URIs at a web server and efficiently discovering updates and additions on subsequent crawls. Our experiments indicated comparable performance for initial crawls, and dramatic increases in update speed mod_oaican also be used to address the representation problem by providing "preservation ready" versions of web resources aggregated with their respective forensic metadata in MPEG-21 DIDL format.
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 …