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共 344 条记录，以下是211-220 订阅

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CSVD: Approximate similarity searches in high dimensional spaces using clustering and singular value decomposition

CSVD: Approximate similarity searches in high dimensional sp...

引用

conference on Multimedia storage and Archiving Systems iii

作者： Thomasian, A Castelli, V Li, CS IBM Corp Thomas J Watson Res Ctr Yorktown Heights NY 10598 USA

ISBN: (纸本)0819429880

Many data-intensive applications, such as content-based retrieval of images or video from multimedia database and similarity retrieval of patterns;in data mining, require the ability the efficiently performing similarity queries. Unfortunately, the performance of nearest neighbor (NN) algorithms, the basis for similarity search, quickly deteriorates with the number of dimensions. In this paper we propose a method called Clustering with Singular Value Decomposition (CSVD), combining clustering and singular value decomposition (SVD) to reduce the number of index dimensions. With CSVD, points are grouped into clusters that are more amenable to dimensionality reduction than the original dataset, Experiments with texture vectors extracted from satellite images show that CSVD achieves significantly higher dimensionality reduction than SVD alone for the satellite fraction of total variance with preserved. Conversely, for thr same compression ratio CSVD results in an increase in preserved total variance with respect to SVD (e.g,, a 70% increase fear a. 20:1 compression ratio). Then, approximate NN queries are more efficiently processed, as quantified through experimental results.

关键词： databases Earth observing sensors Satellite imaging Satellites Data compression Data mining Principal component analysis Feature extraction Multimedia video

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Querying and navigating of multimedia objects

Querying and navigating of multimedia objects

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conference on Multimedia storage and Archiving Systems iii

作者： Chunyan, M Hu, MJ Gintic Inst Mfg Technol Mfg Informat Techol Div Singapore 638075 Singapore

ISBN: (纸本)0819429880

The rapidly growing interest in building up multimedia applications has created a need for applying database technology to multimedia systems, to support the efficient access, query, and retrieval of complex multimedia information. In this paper, an Object Relational Multimedia Data Model (ORMD) has been proposed for modeling of multimedia objects. The ORMD model supports not only various relationships but also the hyper links among the multimedia objects. Therefore, querying and navigating of multimedia objects can be facilitated. Based on this data model, an infrastructure design of multimedia database system has been presented. Multimedia extensions of data types and query language have been designed to facilitate various queries of multimedia objects. Currently, we are implementing a prototype, called Multimedia Information retrieval System to support the efficient querying and navigating of multimedia objects. The development of MIR System shows the potential of features of extending it to diverse multimedia applications, such as digital libraries, Internet video server etc.

关键词： query language SQL3 object-relational database system multimedia data model multimedia databases

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Scene change detection and feature extraction for MPEG-4 sequences

Scene change detection and feature extraction for MPEG-4 seq...

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7th storage and retrieval for image and video databases conference

作者： Divakaran, A Ito, H Sun, HF Poon, T Mitsubishi Elect Informat Technol Amer Adv Televis Lab New Providence NJ 07974 USA

ISBN: (纸本)0819431273

In this paper we present a new computationally efficient and effective technique for detection of abrupt scene changes in MPEG-4/2 compressed video sequences. We combine the de image based approach of Yeo and Liu(1) with the bit allocation change based approach of Feng, Lo and Mehrpour.(2) The bit allocation based approach has the advantage of computational simplicity since it only requires entropy decoding of the sequence. Since extraction of de images from I-Frames/Objects is simple, the de image based technique of Yeo is a good alternative for comparison of I-frames/objects. For P-frames/objects however, Yeo's algorithm requires additional computation. We find that the bit allocation change based approach is prone to false detection in comparison of intra-coded objects in MPEG-4 sequences. However, if a suspected scene/object change has been located accurately in a group of consecutive frames/objects, the bit allocation based technique quickly and accurately locates the cut point therein. This motivates us to use de image based detection between successive I-Frames/Objects to identify the sub-sequences with scene/object changes, and then use bit allocation based detection to find the cut point therein. Our technique thus has only a marginally greater complexity than the completely bit allocation based technique but has greater accuracy. It is applicable to both MPEG-2 sequences and MPEG-4 multiple-object sequences. In the MPEG-4 multiple object case, we use a weighted sum of the change in each object of the frame using the area of the object as the weight.

关键词： compressed-domain video processing video segmentation MPEG-4 MPEG-2 scene change detection

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conference on Multimedia storage and Archiving Systems iii

作者： Squire, DM Univ Geneva Comp Vis Grp CH-1211 Geneva 4 Switzerland

ISBN: (纸本)0819429880

In this paper our goal is to employ human judgments of image similarity to improve the organization of an image database for content-based retrieval. We first derive a statistic, kappa(B), for measuring the agreement between two partitionings of an image set into unlabeled subsets. This measure can be used to measure both the degree of agreement between pairs of human subjects and that between human and machine partitionings of an image set. It also allows a direct comparison of database organizations, as opposed to the indirect measure available via precision and recall measurements. This provides a rigorous means of selecting between competing image database organization systems, and assessing how close the performance of such systems is to that which might be expected from a database organization done by hand. We then use the results of experiments in which human subjects are asked to partition a set of images into unlabeld subsets to define a similarity measure for pairs of images based on the frequency with which they were judged to be similar. We show that, when this measure is used to partition an image set using a clustering technique, the resultant clustering agrees better with those produced by human subjects than any of the feature space-based techniques investigated. Finally, we investigate the use of machine learning techniques to discover a mapping from a numerical feature space to this perceptual similarity space. Such a mapping would allow the ground truth knowledge abstracted from the human judgments to be generalized to unseen images. We show that a learning technique based on an extension of a Kohonen network allows a similarity space to be learnt which results in partitionings in excellent agreement with those produced by human subjects.

关键词： image databases database organization similarity learning agreement

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Fast polynomial regression transform for video database

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IEEE International conference on image Processing

作者： K.J. Han A.H. Tewfik Department of Electrical and Computer Engineering University of Minnesota MN USA

ISBN: (纸本)0818688211

Important issues in multimedia information systems are the development of efficient storage layout models and effective retrieval system to manage multimedia databases. In multimedia information systems, the capability for interaction with video media type is still extremely limited due to a huge amount of video databases. We present the Fast Polynomial Regression Transform (FPRT) based metadata scheme for manipulating the large video database in the paper. This new metadata scheme provides the simplification of the query mechanism and the improvement of communication in multimedia systems. The main advantage of the proposed approach is the reduction of the data storage space while preserving much video content information. Other advantages are computational simplicity for video information coding and accuracy for video indexing. Visual tools for video representation and browsing are also presented.

关键词： Polynomials Multimedia databases Multimedia systems Information retrieval video compression Management information systems Streaming media Space technology Indexing image segmentation

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Dimensionality reduction for similarity searching in dynamic databases

Dimensionality reduction for similarity searching in dynamic...

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Proceedings of the ACM SIGMOD International conference on Management of Data

作者： Kanth, K.V.Ravi Agrawal, Divyakant Singh, Ambuj Univ of California at Santa Barbara Santa Barbara United States

databases are increasingly being used to store multi-media objects such as maps, images, audio and video. storage and retrieval of these objects is accomplished using multi-dimensional index structures such as R*-trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is however accompanied by a loss of precision of query results. Current techniques such as QBIC use SVD transform-based dimensionality reduction to ensure high query precision. The drawback of this approach is that SVD is expensive to compute, and therefore not readily applicable to dynamic databases. In this paper, we propose novel techniques for performing SVD-based dimensionality reduction in dynamic databases. When the data distribution changes considerably so as to degrade query precision, we recompute the SVD transform and incorporate it in the existing index structure. For recomputing the SVD-transform, we propose a novel technique that uses aggregate data from the existing index rather than the entire data. This technique reduces the SVD-computation time without compromising query precision. We then explore efficient ways to incorporate the recomputed SVD-transform in the existing index structure without degrading subsequent query response times. These techniques reduce the computation time by a factor of 20 in experiments on color and texture image vectors. The error due to approximate computation of SVD is less than 10%.

关键词： Distributed database systems

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Dimensionality reduction for similarity searching in dynamic databases 98

Dimensionality reduction for similarity searching in dynamic...

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Proceedings of the 1998 ACM SIGMOD international conference on Management of data

作者： K. V. Ravi Kanth Divyakant Agrawal Ambuj Singh Department of Computer Science University of California Santa Barbara

ISBN: (纸本)9780897919951

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Semantic image retrieval through human subject segmentation and characterization 5

Semantic image retrieval through human subject segmentation ...

引用

conference on storage and retrieval for image and video databases V

作者： Li, YB Tao, B Kei, S Wolf, W Princeton Univ. (United States)

ISBN: (纸本)0819424331

video databases can be searched for visual content by searching over automatically extracted key frames rather than the complete video sequence. Many video materials used in the humanities and social sciences contain a preponderance of shots of people. In this paper, we describe our work in semantic image retrieval of person-rich scenes (key frames) for video databases and libraries. We use an approach called retrieval through segmentation. A key-frame image is first segmented into human subjects and background. We developed a specialized segmentation technique that utilizes both human flesh-tone detection and contour analysis. Experimental results show that this technique can effectively segment images in a low time complexity. Once the image has been segmented, we can then extract features or pose queries about both the people and the background. We propose a retrieval framework that is based on the segmentation results and the extracted features of people and background.

关键词： image retrieval key frame segmentation flesh tone detection contour extraction

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An evaluation of content maintenance in multiresolution image coding 5

An evaluation of content maintenance in multiresolution imag...

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conference on storage and retrieval for image and video databases V

作者： DiLecce, V Guerriero, A DEE - Politecnico di Bari Via Orabona n.4 Bari 70125 Italy

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Virage video engine 5

Virage video engine

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conference on storage and retrieval for image and video databases V

作者： Hampapur, A Gupta, A Horowitz, B Shu, CF Fuller, C Bach, J Gorkani, M Jain, R Virage Inc. (United States)

ISBN: (纸本)0819424331

The temporal and multi-modal nature of video increases the dimensionality of content based retrieval problem. This places new demands on the indexing and retrieval tools required. The Virage video Engine (VVE) with the default set of primitives provide the necessary frame work and basic tools for video content based retrieval. The video engine is a flexible platform independent architecture which provides support for processing multiple synchronized data streams like image sequences, audio and closed captions. The architecture allows for multi-modal indexing and retrieval of video through the use of media specific primitives. This paper presents the use of the VVE framework for content based video retrieval.

关键词： video indexing video retrieval video database content based retrieval image database multimedia database video asset management visual information retrieval

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