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conference on Multimedia storage and Archiving Systems iiI

作者： Furht, B Saksobhavivat, P Florida Atlantic Univ NSF Multimedia Lab Boca Raton FL 33431 USA

ISBN: (纸本)0819429880

In this paper, we present a novel technique that can be used for fast similarity-based indexing and retrieval of both image and video databases in distributed environments. We assume that image or video databases are stored in the compressed form using standard techniques such as JPEG for images, and M-JPEG or MPEG for videos. The existing techniques, proposed in the literature, use computationally intensive features and cost functions for content-based image and video retrieval and indexing. The proposed algorithm uses an innovative approach based on histograms of DC coefficients only, and therefore is computationally less expensive than the other approaches. In the case of a JPEG-compressed image database, the query process is the following. The user submits a request for search-by-similarity by presenting the desired image. The algorithm calculates the DC coefficients of this image and creates the histogram of DC coefficients. Then, the algorithm compares the DC histogram of the submitted image with the DC histograms of the images stored in the database using a histogram similarity metric. The image database can be local or at a remote server. In our experiments, we compared several histogram similarity metrics: weighted Euclidean distance, square difference, and absolute difference. The algorithm then selects and presents to the user the images with the smallest values of the metric that best match the submitted image. In the case of a compressed video database, the similarity-based indexing and retrieval is more complex. The manipulation of a video database consists of three main operations: (1) partitioning of the video into clips, (2) key frame extraction, and (3) indexing and retrieval of key frames. The proposed algorithm has been applied in all three steps. First, the DC histograms are implemented for partitioning each video into clips or camera shots. Then, in the next phase the same DC histograms are used to extract key frames and create a database of ke

关键词： content-based retrieval and indexing multimedia databases DC coefficients histogram of DC coefficients

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A robust approach to video segmentation using compressed data 5

A robust approach to video segmentation using compressed dat...

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conference on storage and retrieval for image and video databases V

作者： Wei, Q Zhang, HJ Zhong, YZ Tsinghua University Department of Computer Science and Technology Beijing 100084 China HP Labs 1501 Page Mill Road Palo Alto 94304 CA United States

ISBN: (纸本)0819424331

Partitioning video sequences into individual shots is one of the fundamental processes in video content parsing and content-based video retrieval. Up to now, a variety of algorithms and systems have been developed to perform this task. However, most of these algorithms exhibit their weakness when applied to detect gradual transitions such as dissolves, wipe, fade-in and fade-out In this paper, we presented an integrated scheme to the detection of abrupt camera breaks and gradual scene changes using DCT coefficients and motion data encoded in the MPEG compression stream. The core of the proposed approach is a tree-like classifier. Three algorithms are organized in the classifier to deal with the complicated situation in real-world video sequences separately.

关键词： video segmentation video database content-based retrieval video compression multimedia

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Combining indexing and learning in iterative refinement

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 390-400页

作者： Li, Chung-Sheng Castelli, Vittorio Smith, John R. Bergman, Lawrence IBM T.J. Watson Research Cent Yorktown Heights United States

A simultaneous learning and indexing technique is proposed for efficient content-based retrieval of images that can be described by feature vectors. This technique builds a compact high-dimensional index while taking into account that the raw feature space needs to be adjusted for each new application. With this technique, much better efficiency can be achieved as compared to those techniques that do not make provisions for efficient indexing.

关键词： image enhancement

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video segmentation using combined cues

Video segmentation using combined cues

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storage and retrieval for image and video databases VI conference

作者： Toller, MS Lewis, PH Nixon, MS Univ Southampton Dept Elect & Comp Sci Multimedia Res Grp Southampton SO17 1BJ Hants England

ISBN: (纸本)0819427527

The use of video data in the multimedia environment is increasing rapidly, and so tools to handle large volumes of video data are required. One of the first steps towards creating more versatile video tools is to segment the video data, i.e. partition it into its component shots. This paper presents a novel combination of algorithms for video segmentation, utilising histogram comparison, motion vector information (focus of expansion), and edge information to detect transitions between shots. Our method can reliably detect transitions such as camera breaks, fades, dissolves and wipes, in video compressed to the MPEG-I standard.

关键词： video segmentation key frame extraction

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Audio-guided audiovisual data segmentation, indexing, and retrieval

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 316-327页

作者： Zhang, Tong Kuo, C.-C.Jay Univ of Southern California Los Angeles United States

While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for automatic segmentation, indexing, and retrieval of audiovisual data based on audio content analysis. The accompanying audio signal of audiovisual data is first segmented and classified into basic types, i.e. speech, music, environmental sound, and silence. This coarse-level segmentation and indexing step is based on morphological and statistical analysis of several short-term features of the audio signals. Then, environmental sounds are classified into finer classes such as applause, explosion, bird's sound, etc. This fine-level classification and indexing step is based on time-frequency analysis of audio signals and the use of hidden Markov model (HMM) as the classifier. On top of this archiving scheme, an audiovisual data retrieval system is proposed. Experimental results show that the proposed approach has an accuracy rate higher than 90% for the coarse-level classification, and higher than 85% for the fine-level classification. Examples of audiovisual data segmentation and retrieval are also provided.

关键词： image segmentation

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image retrieval FOR INFORMATION SYSTEMS

IMAGE RETRIEVAL FOR INFORMATION SYSTEMS

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conference on storage and retrieval for image and video databases iiI

作者： HERMES, T KLAUCK, C KREYSS, J ZHANG, J UNIV BREMEN DEPT COMP SCID-28334 BREMENGERMANY

ISBN: (纸本)081941767X

In order to retrieve a set of intended images from a huge image archive, human beings think of special contents with respect to the searched scene, like a countryside or a technical drawing. Therefore, in general it is harder to retrieve images by using a syntactical feature- based language than a language which offers the selection of examples concerning color, texture, and contour in combination with natural language concepts. This motivation leads to a content-based image analysis and goes on to a content-based storage and retrieval of images. Furthermore, it is unreasonable for any human being to make the content description for thousands of images manually. From this point of view, the project IRIS (image retrieval for information systems) combines well-known methods and techniques in computer vision and AI in a new way to generate content descriptions of images in a textual form automatically. IRIS retrieves the images by means of text retrieval realized by the SearchManager/6000. The textual description is generated by four sub-steps: feature extraction like colors, textures, and contours, segmentation, and interpretation of part-whole relations. The system is implemented on IBM RS/6000 using AIX. It has already been tested with 350 images.

关键词： image retrieval TEXT retrieval image ANALYSIS NATURAL LANGUAGE

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Delaunay triangulation for image object indexing: a novel method for shape representation

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 631-642页

作者： Tao, Yi Grosky, William I. Wayne State Univ Detroit United States

Recent research on image databases has been aimed at the development of content-based retrieval techniques for the management of visual information. Compared with such visual information as color, texture, and spatial constraints, shape is so important a feature associated with those image objects of interest that shape alone may be sufficient to identify and classify an object completely and accurately. This paper presents a novel method based on feature point histogram indexing for object shape representation in image databases. In this scheme, the feature point histogram is obtained by discretizing the angles produced by the Delaunay triangulation of a set of unique feature points which characterize object shape in the context, and then counting the number of times each discrete angle occurs in the resulted triangulation. The proposed shape representation technique is translation, scale, and rotation independent. Our various experiments concluded that the Euclidean distance performs very well as the similarity measure function in combination with the feature point histogram computed by counting the two largest angles of each individual Delaunay triangle. Through the further experiment, we also found evidence that an image object representation using a feature point histogram provides an effective cue for image object discrimination.

关键词： Feature extraction

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Location hashing: an efficient indexing method for locating object queries in image databases

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3656卷 366-378页

作者： Syeda-Mahmood, Tanveer IBM Almaden Research Cent San Jose United States

Queries referring to content embedded within images are an essential component of content-based search, browse, or summarize operations in image databases. Localization of such queries under changes in appearance, occlusions and background clutter, is a difficult problem, for which current spatial access structures in databases are not suitable. In this paper we present a new method of indexing image databases called location hashing that uses a special data structure called the location hash tree (LHT) for organizing feature information from images of a database. Location hashing is based on the principle of geometric hashing and determines simultaneously, the relevant images in the database and the regions within them that are most likely to contain a 2d pattern query without incurring detailed search of either. The location hash tree being a red-black tree, allows for efficient search for candidate locations using pose-invariant feature information derived from the query.

关键词： Database systems

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Efficient image retrieval with multiple distance measures 5

Efficient image retrieval with multiple distance measures

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conference on storage and retrieval for image and video databases V

作者： Berman, A Shapiro, L Univ. of Washington (United States)

ISBN: (纸本)0819424331

There is a growing need for the ability to query image databases based on image content rather than strict keyword search. Most current image database systems that perform query by content require a distance computation for each image in the database. Distance computations can be time consuming, limiting the usability of such systems. There is thus a need for indexing systems and algorithms that can eliminate candidate images without performing distance calculations. As user needs may change from session to session, there is also a need for run-time creation of distance measures. In this paper, we introduce FIDS, or ''Flexible image Database System.'' FIDS allows the user to query the database based on user-defined polynomial combinations of predefined distance measures. Using an indexing scheme and algorithms based on the triangle inequality, FIDS can return matches to the query image without directly comparing the query image to much of the database. FIDS is currently being tested on a database of eighteen hundred images.

关键词： query by content image database triangle inequality distance measure composition

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Developing high-level representations of video clips using video trails

Developing high-level representations of video clips using v...

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storage and retrieval for image and video databases VI conference

作者： Kobla, V Doermann, D Faloutsos, C Univ Maryland Lab Language & Media Proc College Pk MD 20742 USA

ISBN: (纸本)0819427527

A high-level representation of a video clip comprising information about its physical and semantic structure is necessary for providing appropriate processing, indexing and retrieval capabilities for video databases. We describe a novel technique which reduces a sequence of MPEG encoded video frames to a trail of points in a low dimensional space. In our earlier work,(1) we presented techniques applicable in 3-D, but in this paper, we describe techniques that can be extended to higher dimensions where improved performance is expected. In the low-dimensional space, we can cluster frames, analyze transitions between clusters and compute properties of the resulting trail. Portions of the trail can be classified as either stationary or transitional, leading to high-level descriptions of the video. Tracking the interaction of clusters over time, we lay the groundwork for the complete analysis and representation of the video's physical and semantic structure.

关键词： video representation compressed video analysis MPEG FastMap

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