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检索条件"任意字段=Storage and Retrieval for Image and Video Databases II 1994"

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BOUNDS FOR THE DISCRIMINATION POWER OF COLOR INDEXING TECHNIQUES 2

BOUNDS FOR THE DISCRIMINATION POWER OF COLOR INDEXING TECHNI...

引用

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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EVALUATION OF AN APPLICATION-INDEPENDENT image-INFORMATION SYSTEM 2

EVALUATION OF AN APPLICATION-INDEPENDENT IMAGE-INFORMATION S...

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Conference on storage and retrieval for image and video databases ii

作者： OAKLEY, J DAVIS, D SHANN, R XYDEAS, C UNIV MANCHESTER MULTI MEDIA RES GRPMANCHESTER M13 9PLLANCSENGLAND

ISBN: (纸本)0819414808

The Manchester Content Addressable image Database (CAID) is a generic tool which has been designed for image informatics and computer vision problems. The system stores pre- computed feature tokens, which are obtained by conventional processing of the input images, into a database which is accessed by a specialized query language (MVQL). MVQL extends the usual notion of a query language to include creation and refinement of groupings based on the stored attributes of the pre-computed features, and these groupings can be continued in a nested fashion. The aim of this paper is to report on two recent application studies. The first study concerns the automatic registration of volume MR data sets. This is achieved entirely within the CAID environment (i.e., as a database query) using only a short MVQL specification. The method used is based on curve token correspondence and an exhaustive search of transformation space. Some results on the estimated accuracy of the result will be included. The second application is concerned with the classification of microfossil images into morphological groups. Preliminary work on detecting microfossil structures was reported in Shann et al. Here we address the problem of classifying detected structures into six broad morphological groups. This is achieved using MVQL to define `structure' measures from the distribution of curve tokens in a circular region around each microfossil. The results are surprisingly good considering the very limited feature evidence used. Both application studies confirm the general applicability of the CAID structure and its query language.

关键词： Sensors databases Head image registration Magnetic resonance imaging image classification image segmentation Sensor performance image processing image retrieval

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Two-stage strategy for indexing and presenting video 2

Two-stage strategy for indexing and presenting video

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storage and retrieval for image and video databases ii 1994

作者： Cherfaoui, Mourad Bertin, Christian TMM/CCETT 4 rue du Clos courtel Cesson-sevigne35512 France

Owing to the advent of multimedia, simultaneous access 'to text, image, sound, graphics and video has now became been made possible. However, video on computers is a very recent capability. It is achieved thanks to the progress made in hardware components, digitization equipments, storage media (CD ROM) and, above all, image compression techniques (JPEG 1 for still pictures and MPEG 2for motion pictures). The representational power of video makes it the favourite medium for many multimedia applications. The various media are not used in the same way. A structured text (with a table of contents), a still, graphics or sound (with representative graph) may be seen as a whole, allowing them to be handled (for editing purposes for example). Furthermore, these media support information-based navigation (hypertext 3 is a good example of this capability). On the other hand, video is basically a sequential medium. Operations such as fast-forward, rewind and pause allow only limited interactivity when consulting video. This lack of interactivity is due to the fact that video information, unlike structured text, is delivered "flat", with no indications. In order to have the same capacities as in a structured text, it is necessary to have an interpretation level above the raw video information. In the case of structured text, the interpretation level corresponds to paragraph and chapter titles and to the table of contents. Furthermore, text has a basic semantic entity : the word which is used with the search function and the index to create a multiplicity of navigational possibilities through the information. The goal of our work is aimed to offer ways of accessing videos which are similar to those of structured texts. This will make it possible to: .quickly become acquainted with the video content, .quickly access the part of the video of particular interest and .haveentry points in the video. Our methodology is comprised of two stages. In the first stage, we seek to extract t

关键词： video image segmentation Cameras Zoom lenses Visualization image processing video processing video compression image compression Information visualization

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A content-based storage and retrieval scheme for image and video databases

A content-based storage and retrieval scheme for image and v...

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Visual Communications and image Processing 1998 Conference

作者： Herodotou, N Plataniotis, KN Venetsanopoulos, AN Univ Toronto Digital Signal & Image Proc Lab Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

ISBN: (纸本)0819427497

In this paper, a technique is presented to locate and track the facial areas in image and video databases. The extracted facial regions are used to obtain a number of features that are suitable for content-based storage and retrieval. The proposed face localization method consists of essentially two components: i) a color processing unit, and ii) a shape and color analysis module. The color processing component utilizes the distribution of skin-tones in the HSV color space to obtain an initial set of candidate regions or objects. The latter shape and color analysis module is used to correctly identify the facial regions when falsely detected objects are extracted. A number of features such as hair color, skin-tone, and face location and size are subsequently determined from the extracted facial areas. The hair and skin colors provide useful descriptions related to the human characteristics while the face location and size can reveal information about the activity within the scene (i.e. spatial relationships with other objects), and the type of image (i.e. portrait shot, complete body). These features can be effectively combined with others and employed in user queries to retrieve particular facial images.

关键词： facial image databases face location content-based storage/retrieval color segmentation

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Multimedia systems for art and culture: A case study of Brihadisvara temple 5

Multimedia systems for art and culture: A case study of Brih...

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Conference on storage and retrieval for image and video databases V

作者： Jain, AK Goel, S Agarwal, S Mittal, V Sharma, H Mahindru, R Michigan State Univ. (United States) Indira Gandhi National Ctr. for the Arts (India)

ISBN: (纸本)0819424331

In India a temple is not only a structure of religious significance and celebration, but it also plays an important role in the social, administrative and cultural life of the locality. Temples have served as centers for learning Indian scriptures. Music and dance were fostered and performed in the precincts of the temples. Built at the end of the 10th century, the Brihadisvara temple signified new design methodologies. We have access to a large number of images, audio and video recordings, architectural drawings and scholarly publications of this temple. A multimedia system for this temple is being designed which is intended to be used for the following purposes: (i) to inform and enrich the general public, and (ii) to assist the scholars in their research. Such a system will also preserve and archive old historical documents and images. The large database consists primarily of images which can be retrieved using keywords, but the emphasis here is largely on techniques which will allow access using image content. Besides classifying images as either long shots or close-ups, deformable template matching is used for shape-based query by image content, and digital video retrieval. Further, to exploit the non-linear accessibility of video sequences, key frames are determined to aid the domain experts in getting a quick preview of the video. Our database also has images of several old, and rare manuscripts many of which are noisy and difficult to read. We have enhanced them to make them more legible. We are also investigating the optimal trade-off between image quality and compression ratios.

关键词： art and culture content-based retrieval deformable template image compression image enhancement video indexing shot boundary detection key frames

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MALCBR: Content-based retrieval of image databases at multiple abstraction levels

MALCBR: Content-based retrieval of image databases at multip...

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Conference on Multimedia storage and Archiving Systems ii

作者： Castelli, V Li, CS Bergman, LD IBM Thomas J. Watson Research Ctr. (United States)

ISBN: (纸本)0819426628

Content-based search of large image database has received significant attention recently. In this paper, we proposed a new framework, Multiple. Abstraction Level Content Based retrieval (MALCBR), for specifying and process content-based retrieval queries on databases of images, time series, or video data. This framework allows search targets to be expressed in a object-based fashion, that allows the extensible specification of arbitrarily complex queries. In our approach, the search targets are either simple objects, specified at multiple levels of abstraction (pixel, feature and semantic levels), or composite objects, defined as collections of relation on the elements of a set of simple objects. During the search, simple objects at the semantic level are retrieved from database tables, feature level objects are computed using pre-extracted features;appropriately indexed, and pixel level objects are extracted from the raw data. Composite objects are computed at query execution time. This framework provides a powerful mechanism for specifying complicated search target and enable efficient processing of filtering of the search results.

关键词： content-based retrieval image library clustering classification neural networks feature vector template matching

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Synthetic summaries of video sequences using a multiresolution based key frame selection technique in a perceptually uniform color space

Synthetic summaries of video sequences using a multiresoluti...

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IEEE International Conference on image Processing (ICIP 2000)

作者： Campisi, P Neri, A Univ Roma Roma Tre Dipartimento Ingn Elettron I-00146 Rome Italy

ISBN: (纸本)0780362985

video databases are very demanding systems as far as mass storage requirements and computational resources necessary to perform common database operations, such as browsing and retrieval, are required. These operations can be simplified both in terms of computational complexity and of processing time by performing them on an ensemble of frames, called key frames, representative of the content units (shots) in which a video can be segmented. In this contribution an adaptive key frames extraction method based on a wavelet based multiresolution analysis in a perceptually uniform color space is presented. Experimental results that show the effectiveness of the proposed technique to select key frames summarizing the video's content, are finally provided.

关键词： image segmentation

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Scalable near identical image and shot detection 07

Scalable near identical image and shot detection

引用

6th ACM International Conference on image and video retrieval, CIVR 2007

作者： Chum, Ondej Philbin, James Isard, Michael Zisserman, Andrew Department of Engineering Science University of Oxford Microsoft Research Silicon Valley

ISBN: (纸本)1595937331

This paper proposes and compares two novel schemes for near duplicate image and video-shot detection. The first approach is based on global hierarchical colour histograms, using Locality Sensitive Hashing for fast retrieval. The second approach uses local feature descriptors (SIFT) and for retrieval exploits techniques used in the information retrieval community to compute approximate set intersections between documents using a min-Hash algorithm. The requirements for near-duplicate images vary according to the application, and we address two types of near duplicate definition: (i) being perceptually identical (e.g. up to noise, discretization effects, small photometric distortions etc);and (ii) being images of the same 3D scene (so allowing for viewpoint changes and partial occlusion). We define two shots to be near-duplicates if they share a large percentage of near-duplicate frames. We focus primarily on scalability to very large image and video databases, where fast query processing is necessary. Both methods are designed so that only a small amount of data need be stored for each image. In the case of near-duplicate shot detection it is shown that a weak approximation to histogram matching, consuming substantially less storage, is sufficient for good results. We demonstrate our methods on the TRECVID 2006 data set which contains approximately 165 hours of video (about 17.8M frames with 146K key frames), and also on feature films and pop videos. Copyright 2007 ACM.

关键词： image analysis

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Automatic key-frame selection for content-based video indexing and access

Automatic key-frame selection for content-based video indexi...

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Proceedings of the 2000 'storage and retrieval for Media databases 2000'

作者： Toklu, Candemir Liou, Shih-Ping Siemens Corporate Research Inc Princeton United States

This paper addresses key-frame selection for content-based video indexing and access. The proposed key-frame selection method is aimed to operate in real-time irrespective of the available computation resources and memory. Hence, we provide three solutions to content-based key-frame selection with different costs, and suggest three operation levels. The suggested key-frame selection method has two major parts: (i) segmentation of the video into shots;(ii) analysis of the motion and color activity within each video shot to select additional frames. We also provide a new color based approach to key-frame selection and discuss how to fuse color and motion based key-frame selection results.

关键词： image recording

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