41462793
S-STIR: similarity search through iterative refinement
Similarity retrieval of images based on texture and color features has generated a lot of interests recently. Most of these similarity retrievals are based on the computation of the Euclidean distance between the target feature vector and the feature vectors in the database. Euclidean distance, however, does not necessarily reflect either relative similarity required by the user. In this paper, a method based on nonlinear multidimensional scaling is proposed to provide a mechanism for the user to dynamically adjust the similarity measure. The results show that a significant improvement on the precision versus recall curve has been achieved.
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.
1278902
Conceptual modeling of audio-visual content
The explosive growth of applications involving digital audio-visual material is driving the need for more rich content description. The authors present a design process for audio-visual content description. The process involves constructing a conceptual model in which entities, attributes and relationships important for content description are identified and modeled. The procedure provides special handling of different types of spatio-temporal relationships important for audio-visual content modeling. The authors describe the audio-visual content description conceptual modeling methodology in the context of the MPEG-7 description schemes.
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.
38193465
Modeling semantic concepts to support query by keywords in video
Supporting semantic queries is a challenging problem in video retrieval. We propose the use of a lexicon of semantic concepts for handling the queries. We also propose automatic modeling of lexicon items using probabilistic techniques. We use Gaussian mixture models to build computational representations for a variety of semantic concepts including rocket-launch, outdoor greenery, sky etc. Training requires a large amount of annotated (labeled) data. Using the TREC Video test bed we compare the performance of this system supporting query by keywords with the conventional approach of query by example. Results demonstrate significant gains in performance using the automatically learnt models of semantic concepts.
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.
1926668
Exploring "Multiple Worlds" in Parallel
We examine computing alternative solutions to a problem in parallel to improve response time.Problems with exploring multiple alternatives in parallel include (1) side-effects and (2) combinatorial ...
16182080
Self adaptation of mutation rates in a steady state genetic algorithm
This paper investigates the use of genetically encoded mutation rates within a "steady state" genetic algorithm in order to provide a self-adapting mutation mechanism for incremental evolution. One of the outcomes of this work will be a reduction in the number of parameters required to be set by the operator, thus facilitating the transfer of evolutionary computing techniques into an industrial setting. The NK family of landscapes is used to provide a variety of different problems with known statistical features in order to examine the effects of changing various parameters on the performance of the search. A number of policies are considered for the replacement of members of the population with newly created individuals and recombination of material between parents, and a number of methods of encoding for mutation rate are investigated. Empirical comparisons (using the "best-of current-population" metric) over a range of test problems show that a genetic algorithm incorporating the best "flavour" of the adaptive mutation operator outperformed the same algorithm when using any one of a variety of "standard" fixed mutation rates suggested by other authors.
17924974
Towards effective practitioner evaluation: an exploration of issues relating to skills, motivation and evidence
Although academics are increasingly expected to undertake studies of their practice, particularly where this involves the use of learning technology, experience to date suggests that meeting this expectation has proved difficult. This paper attempts to explain this difficulty. After reviewing literature that provides a rationale for practitioner evaluation, the experiences of three projects (EFFECTS, ASTER and SoURCE) which attempted to draw on this process are described. Three main areas of difficulty are discussed: the skills and motivations of the academics involved, and the kinds of evidence (and its analysis) that ‘count’ for a given evaluation. This discussion leads to the identification of a number of problems that inhibit practitioner evaluation, including ambiguity in the nature and purpose of evaluation, and a general feeling that the function of evaluation has already been served through existing quality mechanisms. Finally, the possible implications are considered of some or all of the steps in the evaluation process being undertaken by an evaluator working alongside the academic.
18320669
Operator and parameter adaptation in genetic algorithms
Abstract Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection”. These algorithms maintain a finite memory of individual points on the search landscape known as the “population”. Members of the population are usually represented as strings written over some fixed alphabet, each of which has a scalar value attached to it reflecting its quality or “fitness”. The search may be seen as the iterative application of a number of operators, such as selection, recombination and mutation, to the population with the aim of producing progressively fitter individuals.These operators are usually static, that is to say that their mechanisms, parameters, and probability of application are fixed at the beginning and constant throughout the run of the algorithm. However, there is an increasing body of evidence that not only is there no single choice of operators which is optimal for all problems, but that in fact the optimal choice of operators for a given problem will be time-variant i.e. it will depend on such factors as the degree of convergence of the population. Based on theoretical and practical approaches, a number of authors have proposed methods of adaptively controlling one or more of the operators, usually invoking some kind of “meta-learning” algorithm, in order to try and improve the performance of the Genetic Algorithm as a function optimiser.In this paper we describe the background to these approaches, and suggest a framework for their classification, based on the learning strategy used to control them, and what facets of the algorithm are susceptible to adaptation. We then review a number of significant pieces of work within the context of this setting, and draw some conclusions about the relative merits of various approaches and promising directions for future work.
17447930
Incorporation of adaptive mutation based on subjective evaluation in an interactive evolution strategy
A rapidly emerging model in the field of adaptive computing is the symbiosis of human expertise with evolutionary algorithms for user controlled and directed search. The two aspects in any EA are the selection of individuals to reproduce based on some measure of their quality or fitness and the application of variation operators to produce new solutions. In the context of interactive evolution, these aspects are compounded by the need for rapid convergence to prevent user fatigue and to provide the user some control over the generation of new solutions. Elsewhere, in the work of the authors (2004), we have examined different policies for best incorporating the user into the evaluation and selection process. In this paper, we explore the hypothesis that user assigned fitness represents a source of information that can be used to control the variation process: effectively to broaden the search if none of the current solutions is promising, or focus the search and improve convergence speed in the vicinity of a good solution. The main aims of this study, therefore, are to analyse the advantages of using a user directed adaptive mutation strategy over fixed mutation step sizes in terms of time to converge and robustness of the resulting solution. We present results showing a qualitatively different type of search process can be obtained by using the user assigned fitness to control the nature of the mutation process. There is also a synergy between user-based selection and fitness-based mutation control which out performs either system on its own.