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5th International conference on Information Technology - New Generations

作者： Smith, Mark Khotanzad, Alireza So Methodist Univ Dept Elect Engn Dallas TX 75275 USA

ISBN: (纸本)9780769530994

A novel approach pertaining to the fast and efficient retrieval and storage of video sequences utilizing MPEG-1/2 motion vectors is presented in this paper. A clip first must be segmented into consistent video segments based on the basic editing effects cuts, dissolves, and wipes. All Group of Pictures (GOPs) are then extracted from the clip and decomposed further into I-Frames and P-Frames (B-Frames are disregarded). The initial frame of the sequence is manually segmented into objects, and the selected objects are automatically tracked through the entire sequence using MPEG-1/2 motion vectors. Features pertaining to the edge histogram are extracted from each tracked object (I/P Frames only) and then maintained with the associated frame. An example image or video clip is then presented to the system and the 5 best matching images are retrieved. Results are shown for the standard video sequences such as Foreman, Tennis, etc.

关键词： Database systems

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Archiving and retrieval of sequential images from tomographic databases in PACS

Archiving and retrieval of sequential images from tomographi...

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Proceedings of the 1999 7th conference of the storage and retrieval for image and video databases vII

作者： Shyu, Chi-Ren Cai, T.Tony Broderick, Lynn S. Purdue Univ West Lafayette IN United States

A scheme that reduces the needed storage considerably without reducing the retrieval effectiveness of a content-based image retrieval (CBIR) system such as ASSERT is introduced. This scheme enables ASSERT to retrieve the most similar physician-marked key images from the other patients, and those adjacent images that cohere with the key images. Only the key images and the other images that cohere with the key images are retained for archival purposes. This significantly reduces the amount of storage needed for fast retrieval.

关键词： Database systems

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5thInternational conference on visual Information Systems, vISUAL 2002

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5th International conference on visual Information Systems, vISUAL 2002

ISBN: (纸本)3540433589

The proceedings contain 29 papers. The special focus in this conference is on Content-Based Indexing, Search and retrieval. The topics include: Multi-sensor information fusion by query refinement;a metric distance to compare segmented images;coarse segmentation and fine color description;fast approximate nearest-neighbor queries in metric feature spaces by buoy indexing;a binary color vision framework for content-based image indexing;region-based image retrieval using multiple-features;a Bayesian method for content-based image retrieval by use of relevance feedback;color image retrieval based on primitives of color moments;invariant feature extraction and object shape matching using gabor filtering;a framework for visual information retrieval;feature extraction and a database strategy for video fingerprinting;search, annotate and organize images by groups;an efficient storage organization for multimedia databases;unsupervised categorization for image database overview;a data-flow approach to visual querying in large spatial databases;rate shaping and error concealment;a receiver-driven channel adjustment scheme for periodic broadcast of streaming video;video object hyper-links for streaming applications;fast text caption localization on video using visual rhythm;a new digital watermarking technique for video;automatic closed caption detection and font size differentiation in mpeg video;motion activity based shot identification and closed caption detection for video structuring;visualizing the construction of generic bills of material and data and knowledge visualization in knowledge discovery process.

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image indexing using composite regional color channels features

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 492-500页

作者： Appas, Ahmed R. Darwish, Ahmed M. El-Desouki, Ayman I. Shaheen, Samir I. Electronic Research Inst Dokki Egypt

Color indexing is a technique by which images in the database could be retrieved on the bases of their color content. In this paper, we propose a new set of color features for representing color images, and show how they can be computed and used efficiently to retrieve images that possess certain similarity. These features are based on the first three moments of each color channel. Two differences distinguish this work from previous work reported in the literature. First, we compute the third moment of the color channel distribution around the second moment not around the first moment. The second moment is less sensitive to small luminance changes, than the first moment. Second we combine all three moment values in a single descriptor. This reduces the number of floating point values needed to index the image and hence speeds up the search. To give the user flexibility in terms of defining his center of attention during query time, the proposed approach divides the image into five geometrical regions and allows the user to give different weights for each region to designate its importance. The approach has been tested on databases of 205 images of airplanes and natural scenes. It proved to be insensitive to small rotations and small translations in the image and yielded a better hit rate than similar algorithms previously reported in the literature.

关键词： image analysis

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FISH: A practical system for fast interactive image search in Huge databases

FISH: A practical system for fast interactive image search i...

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2008 International conference on image and video retrieval, CIvR 2008

作者： Tandon, Pradhee Nigam, Piyush Pudi, vikram Jawahar, C.v. International Institute of Information Technology Hyderabad India

ISBN: (纸本)9781605580708

The problem of search and retrieval of images using relevance feedback has attracted tremendous attention in recent years from the research community. A real-world-deployable interactive image retrieval system must (1) be accurate, (2) require minimal user-interaction, (3) be efficient, (4) be scalable to large collections (millions) of images, and (5) support multi-user sessions. For good accuracy, we need effective methods for learning the relevance of image features based on user feedback, both within a user-session and across sessions. Efficiency and scalability require a good index structure for retrieving results. The index structure must allow for the relevance of image features to continually change with fresh queries and user-feedback. The state-of-the-art methods available today each address only a subset of these issues. In this paper, we build a complete system FISH - Fast image Search in Huge databases. In FISH, we integrate selected techniques available in the literature, while adding a few of our own. We perform extensive experiments on real datasets to demonstrate the accuracy, efficiency and scalability of FISH. Our results show that the system can easily scale to millions of images while maintaining interactive response time. Copyright 2008 ACM.

关键词： Scalability

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OPTICAL DATA storage

OPTICAL DATA STORAGE

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conference on Advanced image and video Communications and storage Technologies

作者： PETROv, v Ulm Ger

ISBN: (纸本)0819418021

various modes of optical data storage are regarded. Basic practical systems for optical data storage of 2-D and 3-D images are systematized into groups characterized by similar means of data capture, recording and presentation. Analogue, digital, and interference modes of data capture utilizing only one recording media, as well as updatable and rewriteable recording media, are surveyed. Classifications are given. Novel terminology is introduced. Novel approach to 3-D data presentation is formulated.

关键词： Optical storage Data storage Computing systems visualization Digital recording Holography Photography Silver 3D modeling databases

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Integrated system for image storage, retrieval and transmission using wavelet transform

Integrated system for image storage, retrieval and transmiss...

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Proceedings of the 1999 7th conference of the storage and retrieval for image and video databases vII

作者： Yu, Dan Liu, Ya Mu, Yan Yang, Shiqiang Tsinghua Univ Beijing China

A highly integrated wavelet-based image management system is proposed. Three solutions for key aspect of image management are derived: content-based image retrieval (CBIR);image compression/decompression;and image transmission. By exploring the excellent features of wavelet, integrating key aspect of image management, the system shows a high overall performance.

关键词： Database systems

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Parsing Tv programs for identification and removal of non-story segments

Parsing TV programs for identification and removal of non-st...

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7th storage and retrieval for image and video databases conference

作者： McGee, T Dimitrova, N Philips Res Briarcliff Manor NY 10510 USA

ISBN: (纸本)0819431273

Abstr. video information automatically from the Tv broadcast requires reliable methods for isolating program and commercial segments out of the full broadcast material. In this paper we present the results from cut, static sequence, black frame and text detection for the purpose of isolating non-program segments. These results are evaluated by comparison to human visual inspection using over 13 hours of varied program content. Using cut rate detection alone produced a high recall with a medium precision. Text detection was performed on the commercials and the false positive segments. Adding text detection slightly lowers the recall, however, much higher precision is achieved. A new fast black frame detector algorithm is presented. Black frame detection is important for identifying the commercial boundaries. The results indicate that adding the detection of text in addition to cut rate to reduce the number of false positives appears to be a promising method. Furthermore, by adding the information about the position and size of the text and tracking it through an area should further increase the reliability.

关键词： commercial detection video segmentation video content analysis video parsing

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An efficient content-based video retrieval for large databases

An efficient content-based video retrieval for large databas...

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IEEE International conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Cedillo-Hernandez, Antonio Cedillo-Hernandez, Manuel Garcia-Ugalde, Francisco Nakano-Miyatake, Mariko Perez-Meana, Hector Univ Nacl Autonoma Mexico Fac Ingn Div Ingn Elect Mexico City 04510 DF Mexico Inst Politecn Nacl Escuela Super Ingn Mecan & Elect Mexico City DF Mexico

ISBN: (纸本)9781467383295

Multimedia data grows fast due to advances in information technologies, creating the demand for efficient video indexing and object retrieval techniques. Traditional methods consume significant computational resources such as storage space and processing time. In this paper we propose an efficient content-based video retrieval system that is based on three main stages. The first stage involves computing the DC-image of each I-frame, from which a summarization process to extract key-frames is performed. During the second stage, a segmentation processes is applied to each key-frame in order to isolate the region of interest within it. Local features are extracted from the resulting area and are stored as the descriptor of the frame. The retrieval stage is carried out by computing the Euclidean distance and determines if its content is related with the video database. Experimental results show that the proposed approach is promising in terms of efficiency and effectiveness.

关键词： Efficient CBvR system video indexing DC-frame SURF

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Unsupervised view and rate invariant clustering of video sequences

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COMPUTER vISION AND image UNDERSTANDING 2009年第3期113卷 353-371页

作者： Turaga, Pavan veeraraghavan, Ashok Chellappa, Rama Univ Maryland Ctr Automat Res Dept Elect & Comp Engn UMIACS College Pk MD 20742 USA

videos play an ever increasing role in our everyday lives with applications ranging from news, entertainment, scientific research, security and surveillance. Coupled with the fact that cameras and storage media are becoming less expensive, it has resulted in people producing more video content than ever before. This necessitates the development of efficient indexing and retrieval algorithms for video data. Most state-of-the-art techniques index videos according to the global content in the scene such as color, texture, brightness, etc. In this paper, we discuss the problem of activity-based indexing of videos. To address the problem, first we describe activities as a cascade of dynamical systems which significantly enhances the expressive power of the model while retaining many of the computational advantages of using dynamical models. Second, we also derive methods to incorporate view and rate-invariance into these models so that similar actions are clustered together irrespective of the viewpoint or the rate of execution of the activity. We also derive algorithms to learn the model parameters from a video stream and demonstrate how a single video sequence may be clustered into different clusters where each cluster represents an activity. Experimental results for five different databases show that the clusters found by the algorithm correspond to semantically meaningful activities. (C) 2008 Elsevier Inc. All rights reserved.

关键词： video clustering Summarization Surveillance Cascade of linear dynamical systems view invariance Affine invariance Rate invariance

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