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conference on storage and retrieval for image and video databases II

作者： STRICKER, MA SWISS FED INST TECHNOL COMMUN TECHNOL LABCH-8092 ZURICHSWITZERLAND

ISBN: (纸本)0819414808

Most color indexing techniques proposed in the literature are similar: images are represented by color histograms, and a metric on the color histogram space is used to determine the similarity of images. In this paper we determine the limits of these color indexing techniques. We propose two functions to measure the discrimination power of indexing techniques: the capacity (how many distinguishable histograms can be stored) and the maximal match number (the maximal number of retrieved images). We derive bounds for these functions. These bounds have two practical aspects. First, they help a user to decide whether color histograms effectively index database images from a given domain. Second, they facilitate the choice of a good threshold for the distance below which histograms are considered similar. Our arguments are based on an analysis of the metrical properties of the histogram space and results from coding theory. The results show that over a large range of reasonable parameters the capacity is very large. Thus, the set of parameters for which color indexing works well can be described as the set of parameters for which the maximal match number is below an application-dependent maximum.

关键词： databases image retrieval Coding theory Binary data Distance measurement Data modeling Algorithm development Vector spaces Computer science

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Indexing in video databases

Indexing in video databases

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storage and retrieval for image and video databases iii

作者： Hampapur, Arun Jain, Ramesh C. Weymouth, Terry E. Univ. of Michigan Ann Arbor MI USA

ISBN: (纸本)081941767X

A video database provides content based access to video. This is achieved by organizing or indexing video data based on some set of features. This paper defines the problem of video indexing based on video data models. The procedure required to index video data is outlined. The use of semi-automatic techniques to speed up the indexing processes are explored. These techniques use image motion features to aid in the indexing process. The techniques developed have been applied to video data from cable television feed.

关键词： Indexing (of information)

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videobook: an experiment in characterization of video

Videobook: an experiment in characterization of video

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Proceedings 1996 International conference on image Processing, ICIP'96

作者： Iyengar, Giridharan Lippman, Andrew B. MIT Media Lab Cambridge MA United States

In this paper we present a framework for content based query and retrieval of information from large video databases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, texture and colorimetry cues. This characterization is biologically inspired and results in a compact parameter space where every segment of video is represented by an 8 dimensional vector. Searching and retrieval is done in real-time with high accuracy in this parameter space. The present version of the videoBook has 165 video sequences, each 15 seconds long at 30 frames a second representing storage of 65 Giga Bytes. The videoBook is able to search and retrieve video sequences with 92% accuracy in real-time. Experiments thus demonstrate that the characterization is capable of extracting higher level structure from raw pixel values.

关键词： image processing

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Multi-media indexing over the web 5

Multi-media indexing over the web

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conference on storage and retrieval for image and video databases V

作者： Agnew, B Faloutsos, C Wang, ZY Welch, D Xue, XG Univ. of Maryland/College Park (United States) Univ. of Maryland/College Park and U.S. Army (United States)

ISBN: (纸本)0819424331

There has been work on database systems that can retrieve multimedia objects by their content. We are extending this work by using the World Wide Web as source and storage for multimedia objects much like current text search engines do for textual information. A system that can access all types of multimedia objects by their content is a formidable task and improvements are constantly being made to indexing techniques. We have taken an important first step in demonstrating the viability of this technique while laying the groundwork for a larger, more capable system. We have implemented a simple indexing scheme while concentrating on building the infrastructure to support this system. Our system can retrieve references to images on the WWW, index those images, and store those images using spatial access methods. We then use query by example to find a set of images on the WWW that resemble our query image. Due to its design, it is easy to include additional context features, to substitute different indexing schemes, and add other types of multimedia to our system like time sequences, voice and video.

关键词： multimedia image indexing spatial database content-based retrieval World Wide Web

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video segmentation in the wavelet domain

Video segmentation in the wavelet domain

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conference on Multimedia storage and Archiving Systems iii

作者： Mandal, MK Panchanathan, S Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada

ISBN: (纸本)0819429880

Automatic video indexing is an important feature in the design of a video databases. Recently, compressed domain techniques have become popular due their inherent advantages of efficiency and reduced complexity. Wavelet transform is emerging as a powerful tool for efficient compression of visual information. A variety of wavelet based video compression techniques have been reported in the literature. However, there has been little work done in the area of video indexing in the wavelet domain. In this paper, we present video segmentation techniques in a wavelet based compression framework. These techniques employ wavelet coefficients, their distribution, and the motion vectors estimated by the associated video coder. Simulation result shows that the proposed techniques provide a good indexing performance at a low complexity.

关键词： video segmentation indexing content-based retrieval wavelets motion vectors

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Feature identification as an aid to content-based image retrieval

Feature identification as an aid to content-based image retr...

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storage and retrieval for image and video databases iii

作者： Ramesh, Nagarajan Sethi, Ishwar K. Wayne State Univ. Detroit MI USA

ISBN: (纸本)081941767X

In recent years, databases have evolved from storing pure textual information to storing multimedia information - text, audio, video, and images. With such databases comes the need for a richer set of search keys that include keywords, shapes, sounds, examples, sketches, color, texture and motion. In this paper we address the problem of image retrieval where keys are object shapes or user sketches. In our scheme, shape features are extracted from each image as it is stored. The image is first segmented and points of high curvature are extracted. Regions surrounding the points of high curvature are used to compute feature values by comparing the regions with a number of references. The references themselves are picked out from the set of orthonormal wavelet basis vectors. An ordered set of distance measures between each local region and the wavelet references form a feature vector. When a user queries the database through a sketch, the feature vectors for high curvature points on the sketch are determined. An efficient nearest neighbor search then yields a set of images which contain objects that match the user's sketch closely. The process is completely automated. Initial experimental results are presented.

关键词： Information retrieval systems

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Multifeature image and video content-based storage and retrieval

Multifeature image and video content-based storage and retri...

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conference on Multimedia storage and Archiving Systems

作者： Ardizzone, E LaCascia, M Univ. of Palermo (Italy)

ISBN: (纸本)0819423181

In this paper we present most recent evolution of JACOB, a system we developed for image and video content-based storage and retrieval. The system is based on two separate archives: a ''Features DB'' and a ''Raw-data DB''. When a user puts a query, a search is done in the ''Features DB'';the selected items are taken from the ''Raw-data DB'' and shown to the user. Two kinds of sessions are allowed: ''database population'' and ''database querying''. During a ''database population'' session the user inserts new data into the archive. The input data can consist of digital images or videos. videos are split into shots and for each shot one or more representative frames (r-frames) are automatically extracted. Shots and r-frames are then characterized, either in automatic or semi-automatic way, and stored in the archives. Automatic features' extraction consists of computing some low-level global features. Semi-automatic features' extraction is done by using annotation tools that perform operations that aren't currently possible with fully automatic methods. To this aim semi-automatic motion based segmentation and labeling tools have been developed. During a ''database querying'' session, queries direct or by example are allowed. Queries (direct or by example) may be iterated and variously combined to satisfy the query in the smallest number of steps. Multifeature querying is based on statistical analysis of the feature space.

关键词： databases video Feature extraction image segmentation Motion models image retrieval Zoom lenses Optical flow Computing systems image storage

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Comparison of automatic shot boundary detection algorithms

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 290-301页

作者： Lienhart, Rainer Intel Corp Santa Clara United States

Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its basic components, the shots, only few comparative investigations on early shot boundary detection algorithms have been published. These investigations mainly concentrate on measuring the edit detection performance, however, do not consider the algorithms' ability to classify the types and to locate the boundaries of the edits correctly. This paper extends these comparative investigations. More recent algorithms designed explicitly to detect specific complex editing operations such as fades and dissolves are taken into account, and their ability to classify the types and locate the boundaries of such edits are examined. The algorithms' performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences. The experiments show that while hard cuts and fades can be detected reliably, dissolves are still an open research issue. The false hit rate for dissolves is usually unacceptably high, ranging from 50% up to over 400%. Moreover, all algorithms seem to fail under roughly the same conditions.

关键词： image analysis

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Managing compressed multimedia data in a memory hierarchy: Fundamental issues and basic solutions

Managing compressed multimedia data in a memory hierarchy: F...

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conference on Multimedia storage and Archiving Systems iii

作者： Veijalainen, J Ojaneu, E Univ Jyvaskyla Dept Comp Sci & Informat Syst FIN-40351 Jyvaskyla Finland

ISBN: (纸本)0819429880

The purpose of the work is to discuss the fundamental issues and solutions in managing compressed and uncompressed multimedia data, especially voluminous continuous mediatypes (video, audio) and text in a memory hierarchy with four levels (main memory, magnetic disk, (optical or magnetic) on-line/near-line low-speed memory, and slow off-line memory, i.e. archive). We view the multimedia data in such a database to be generated, (compressed), and stored into the memory hierarchy (at the lowest non-archiving level), and subsequently retrieved, (decompressed), and presented. If unused, the data either travels down in the memory hierarchy or it is compressed and stored at the same level. We first discuss the general prerequisites of the memory hierarchy, like program locality and decreasing storage costs and performance of each deeper level. To discuss the issues in a greater depth a schematic four level memory hierarchy model is presented. Multimedia data poses, as compared to conventional data, three new requirements for a memory hierarchy. First, continuous multimedia data (e.g. audio and especially video) have real-time requirements for the retrieval time, not present in a conventional memory hierarchy supporting e.g. a virtual memory. Second, single multimedia objects are often very large, requiring hundreds of megabytes, even gigabytes of memory. From the memory hierarchy point of view the latter fact necessitates partial storage strategies at different levels. Third, the data is so voluminous that compression becomes an interesting alternative, because of considerable savings in storage capacity and I/O and network bandwith. Based on the real time requirements of continuous multimedia data one can set boundaries for the maximum retrieval time Tr-max Further, knowing the average retrieval speed S-i of the particular memory level i for an arbitrary object X one can determine the deepest possible (i.e. slowest) level the data can be placed on. The inequality Tr(O-j)

关键词： Multimedia video databases Data storage video compression Magnetism Data modeling image compression Optical storage Data archive systems

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image categorization using NxM-grams 5

Image categorization using NxM-grams

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conference on storage and retrieval for image and video databases V

作者： Soffer, A Univ. of Maryland/Baltimore County and NASA Goddard Space Flight Ctr. (United States)

ISBN: (纸本)0819424331

A method for categorizing images using N x M-grams is presented. The goal of categorization is to find all images from the same category as a given query image. Some example categories are hand-written documents, printed documents, floor plans, satellite images, and fingerprints. The categorization method is based on the N-gram technique that is commonly used for determining similarity of text documents. Intuitively an N x M-gram is a small pattern in an image. The hypothesis that two images that have the same recurring patterns are likely to belong to the same category is examined. The notion of N x M-grams is defined and the process of computing an image profile in terms of its N x M-grams termed an N x M-gram vector is explained. Two similarity measures to compare images based on their N x M-gram vectors are proposed. Results of an experiment on images from various categories are presented. The two similarity measures for N x M-gram vectors are compared to each other as well as to results of categorization using a method based on color distribution features. The results show that for our test images N x M-gram based methods were more successful in finding images from the same category as a given query image than color distribution based methods.

关键词： retrieval by content image categorization N-grams image similarity image databases document analysis

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