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conference on Multimedia storage and Archiving Systems

作者： Kobla, v Doermann, D Lin, KI Univ. of Maryland/College Park (United States)

ISBN: (纸本)0819423181

Fast and efficient storage, indexing, browsing, and retrieval of video is a necessity for the development of various multimedia database applications. This can be achieved by analyzing the video directly in the compressed domain, thereby avoiding the overhead of decompressing video into individual frames in the pixel domain. Our compressed domain parsing of video performs shot change detection and motion detection using the data readily accessible from MPEG, with minimal decoding. Key frames are identified and are used for indexing, retrieval, and browsing. In this paper, we describe feature extraction and key frame indexing and retrieval techniques that are directly applicable to compressed video. The features are derived from the available DCT, macroblock, and motion vector information and the techniques enable fast parsing and archiving of video.

关键词： video databases video segmentation video indexing cut detection compressed-domain analysis MPEG FastMap

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Identifying sports videos using replay, text, and camera motion features

Identifying sports videos using replay, text, and camera mot...

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conference on storage and retrieval for Media databases 2000

作者： Kobla, v DeMenthon, D Doermann, D Univ Maryland Lab Language & Media Proc College Pk MD 20742 USA

ISBN: (纸本)0819435902

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in video, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion, and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93%.

关键词： Database systems

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Multimedia information retrieval by analysing content and learning from examples

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 63-74页

作者： Ganapathy, S.Kicha Lei, Zhibin Safranek, Robert J. Bell Lab Murray Hill United States

Multimedia Information Systems are experiencing a tremendous growth as a direct consequence of the popularity and pervasive use of world wide web. As a consequence, it is becoming increasingly important to provide efficient and flexible solutions for accessing and retrieving multimedia data. images and video are emerging as significant data types in multimedia systems. And yet, most commercial systems are still text and key-word based and do not fully exploit the image content of these systems. We believe that there is an opportunity to build a novel interactive multimedia system for some specific applications in electronic commerce. In this paper we present an overview of our approach, the rationale behind it and the problems that are inherent in building such a system. We address some of the technical issues in representing and analysing image primitive features. These are the building blocks of any such systems. They can be generalized into a much broader range of applications as well.

关键词： Multimedia systems

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Model-based semantic object extraction for content-based video representation and indexing

Model-based semantic object extraction for content-based vid...

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conference on storage and retrieval for Media databases 2001

作者： Fan, J Yau, DKY Hacid, MS Elmagarmid, AK Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)0819439932

This paper proposes an integrated system for supporting content-based video retrieval and browsing over networks. An automatic semantic video object extraction technique for providing more compact video representation is developed. The video images are first partitioned into a set of homogeneous regions with accurate boundaries by integrating the results of color edge detection and region growing procedures. The object seeds, which are the intuitive and representative part of the semantic objects, are detected from these obtained homogeneous image regions. The semantic objects are then generated by a seeded region aggregation or a human interaction procedure. These obtained semantic objects are tracked along the time axis for exploiting their temporal correspondences among frames. Given the semantic video objects represented by a set of visual features, a seeded semantic video content clustering technique is developed for providing more effective video indexing, retrieval and browsing.

关键词： object extraction tracking video representation clustering indexing retrieval and browsing

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Efficient image indexing techniques in the JPEG2000 domain

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JOURNAL OF ELECTRONIC IMAGING 2004年第1期13卷 182-190页

作者： Mandal, MK Liu, CP Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2V4 Canada

The application of images and video has increased significantly in recent years. It is important to develop indexing techniques for searching images and video in the compressed domain. Among the compression techniques, discrete-wavelet-transform based techniques have become popular because of their excellent energy compaction and multiresolution capability. As a result, the newly established JPEG2000 image compression standard is based on discrete wavelet transform. We propose two progressive image indexing techniques in the JPEG2000 framework. In the first technique, a significant bitmap and a 2-D histogram of significant bits are used as the image index. In the second technique, a vector comprising variance and mean of the numbers of bilplanes used to encode individual code blocks is employed as the image index. The proposed index can be generated easily from the packet header of a JPEG2000 compressed image, resulting in a very fast search and retrieval. Experimental results show that the proposed techniques provide good indexing performance. (C) 2004 SPIE and IST.

关键词： image retrieval JPEG2000 Wavelets databases Discrete wavelet transforms image compression Binary data Raster graphics image resolution Tolerancing

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REAL-TIME OBJECT EXTRACTION SYSTEM WITH SEQUENTIAL GROWING 2

REAL-TIME OBJECT EXTRACTION SYSTEM WITH SEQUENTIAL GROWING

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conference on storage and retrieval for image and video databases II

作者： NISHIMURA, R ODA, M NONAKA, S IMAIDE, T HITACHI LTD IMAGE & MEDIA SYST LABTOTSUKA KUYOKOHAMA 244JAPAN

ISBN: (纸本)0819414808

This paper describes a novel system for real-time object extraction from a moving video image. The object extraction method employed in this system has two features. The first one is multi-channel thresholding in a color space for extracting a target with several colors as a single object. The color space is normalized by luminance to make the process robust against light intensity fluctuations. The other feature is a key algorithm, called sequential growing, which exploits interfield correlation of a video image and realizes field-rate operation. In this algorithm, a binary image representing a target object is generated by growing an initially given mask image horizontally and vertically until whole object is extracted. We have also fabricated a 0.8 micrometers CMOS chip to incorporate the system into a compact video camera, which has successfully extracted objects in a number of general scenes.

关键词： video Cameras Detection and tracking algorithms Imaging systems Binary data image processing Signal processing Digital signal processing Feature extraction Seaborgium

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Hierarchical clustering algorithm for fast image retrieval

Hierarchical clustering algorithm for fast image retrieval

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7th storage and retrieval for image and video databases conference

作者： Krishnamachari, S Abdel-Mottaleb, M Philips Res Labs Briarcliff Manor NY 10510 USA

ISBN: (纸本)0819431273

image retrieval systems that compare the query image exhaustively with each individual image in the database are not scalable to large databases. A scalable search system should ensure that the search time does not increase linearly with the number of images in the database. We present a clustering based indexing technique, where the images in the database are grouped into clusters of images with similar color content using a hierarchical clustering algorithm. At search time the query image is not compared with all the images in the database, but only with a small subset. Experiments show that this clustering based approach offers a superior response time with a high retrieval accuracy. Experiments with different database sizes indicate that for a given retrieval accuracy the search time does not increase linearly with the database size.

关键词： image retrieval color histogram scalable clustering hierarchical

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Fast encryption of image data using chaotic Kolmogorov flows 5

Fast encryption of image data using chaotic Kolmogorov flows

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conference on storage and retrieval for image and video databases v

作者： Scharinger, J Johannes Kepler Univ. Linz (Austria)

ISBN: (纸本)0819424331

To guarantee security and privacy A image transmission and archival applications, adequate efficient bulk encryption techniques are necessary which are able to cope with the vast amounts of image data involved. Experience has shown that block-oriented symmetric product ciphers constitute an adequate design paradigm for resolving this task, since they can offer a very high level of security as well as very high encryption rates. In this contribution we introduce a new product cipher which encrypts large blocks of plain-text (images) by repeated intertwined application of substitution and permutation operations. While almost all of the current product ciphers use fixed (predefined) permutation operations on small data blocks, our approach involves parameterizable (keyed) permutations on large data blocks (whole images) induced by specific chaotic systems (Kolmogorov flows). By combining these highly unstable dynamics with an adaption of a very fast shift register based pseudo-random number generator we obtain a new class of computationally secure product ciphers which are firmly grounded on systems theoretic concepts, offering many features that make them superior to contemporary bulk encryption systems when aiming at efficient image data encryption.

关键词： image encryption product ciphers chaotic systems Kolmogorov hows pseudo-random number generation shift registers

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Augmented image histogram for image and video similarity search

Augmented image histogram for image and video similarity sea...

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7th storage and retrieval for image and video databases conference

作者： Chen, Y Wong, EK Polytech Univ Dept Informat & Comp Sci Brooklyn NY 11201 USA

ISBN: (纸本)0819431273

image histogram is an image feature widely used in content-based image retrieval and video segmentation. It is simple to compute yet very effective as a feature in detecting image-to-image similarity, or frame-to-frame dissimilarity. While the image histogram captures the global distribution of different intensities or colors well, it does not contain any information about the spatial distribution of pixels. In this paper, we propose to incorporate spatial information into the image histogram by computing features from the spatial distance between pixels belonging to the same intensity or color. In addition to the frequency count of the intensity or color, the mean, variance, and entropy of the distances are computed to form an Augmented image Histogram. Using the new feature, we preformed experiments on a set of color images and a color video sequence. Experimental results demonstrate that the Augmented image Histogram performs significantly better than the conventional color histogram, both in image retrieval and video shot segmentation.

关键词： content-based image retrieval video shot segmentation augmented image histogram similarity search spatial information

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New anchor selection methods for image retrieval

New anchor selection methods for image retrieval

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conference on storage and retrieval for Media databases 2003

作者： Natsev, A Smith, JR IBM Corp TJ Watson Res Ctr Hawthorne NY 10532 USA

ISBN: (纸本)0819448214

Anchoring is a technique for representing objects by their distances to a few well chosen landmarks, or anchors. Objects are mapped to distance-based feature vectors, which can be used for content-based retrieval, classification, clustering, and relevance feedback of images, audio, and video. The anchoring transformation typically reduces dimensionality and replaces expensive similarity computations in the original domain with simple distance computations in the anchored feature domain, while guaranteeing lack of false dismissals. Anchoring is therefore surprisingly simple, yet effective, and flavors of it have seen application in speech recognition, audio classification, protein homology detection, and shape matching. In this paper, we describe the anchoring technique in some detail and study methods for anchor selection, both from an analytical, as well as empirical, standpoint. Most work to date has largely ignored this problem by fixing the anchors to be the entire set of objects or by using greedy selection from among the set of objects. We generalize previous work by considering anchors from outside of the object space, and by deriving an analytical upper bound on the distance-approximation error of the method.

关键词： image retrieval databases Error analysis Feature extraction vector spaces video image classification Proteins Transform theory visualization

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