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检索条件"任意字段=Conference on Storage and Retrieval for Image and Video Databases V"

共 403 条记录，以下是251-260 订阅

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image indexing using composite regional color channels features

Image indexing using composite regional color channels featu...

引用

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

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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vORTEX: video retrieval and tracking from compressed multimedia databases - Template matching from MPEG2 video compression standard

VORTEX: Video retrieval and tracking from compressed multime...

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conference on Multimedia storage and Archiving Systems III

作者： Schonfeld, D Lelescu, D Univ Illinois EECS Dept Signal & Image Res Lab Chicago IL 60607 USA

ISBN: (纸本)0819429880

In this paper, a novel visual search engine for video retrieval and tracking from compressed multimedia databases is proposed. Our approach exploits the structure of video compression standards in order to perform object matching directly on the compressed video data. This is achieved by utilizing motion compensation-a critical prediction filter embedded in video compression standards-to estimate and interpolate the desired method for template matching. Motion analysis is used to implement fast tracking of objects of interest on the compressed video data. Being presented with a query in the form of template images of objects, the system operates on the compressed video in order to find the images or video sequences where those objects are present and their positions in the image. This in turn enables the retrieval and display of the query-relevant sequences.

关键词： video retrieval compressed multimedia databases compressed domain processing motion analysis MPEG

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vORTEX: video retrieval and tracking from compressed multimedia databases - affine transformation and occlusion invariant tracking from MPEG-2 video

VORTEX: video retrieval and tracking from compressed multime...

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7th storage and retrieval for image and video databases conference

作者： Schonfeld, D Lelescu, D Univ Illinois Dept EECS Signal & Image Res Lab Chicago IL 60680 USA

ISBN: (纸本)0819431273

In this paper, we present topics related to tracking of video objects in compressed video databases in the context of video retrieval applications. We developed a video retrieval and tracking system (vORTEX) to enable operation directly on compressed video data. The structure of the video compression standards is exploited in order to avoid the costly decompression operation. This is achieved by utilizing motion compensation-a critical prediction filter embedded in video compression standards-to estimate and interpolate the desired method for template matching. Occlusion analysis, filtering and motion analysis are used to implement fast tracking of objects of interest on the compressed video data. Being presented with a query in the form of template images of objects, the system operates on the compressed video in order to find the images or video sequences where those objects are present and their positions in the image. This enables the retrieval and display of the query-relevant sequences.

关键词： video retrieval compressed multimedia databases compressed domain processing motion analysis occlusion MPEG

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Proceedings of SPIE: storage and retrieval for image and video databases vI

Proceedings of SPIE: Storage and Retrieval for Image and Vid...

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storage and retrieval for image and video databases vI

This volume 3312 of the conference proceedings contains 40 papers. Topics discussed include image retrieval, video representation, video segmentation, intelligent tools, similarity search, image and video authenticati... 详细信息

关键词： Digital image storage

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Eigendecomposition-based analysis of video images

Eigendecomposition-based analysis of video images

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7th storage and retrieval for image and video databases conference

作者： Chang, CY Maciejewski, AA Balakrishnan, v Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)0819431273

We present a fast algorithm for computing the singular value decomposition (SvD) of a matrix consisting of the frames from a video sequence. The computational efficiency of this algorithm derives from the observation that portions of a video sequence will consist of sets of correlated frames. We then show that the information obtained from the SvD can be used to analyze video sequences to obtain information such as scene breaks, scene query, reduced-order shot representation and key frame determination. We illustrate this approach on several video sequences.

关键词： eigenimages eigendecomposition singular value decomposition (SvD) video analysis

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A fast content-based multimedia retrieval technique using compressed data

A fast content-based multimedia retrieval technique using co...

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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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image content retrieval from image databases using feature integration by Choquet integral

Image content retrieval from image databases using feature i...

引用

7th storage and retrieval for image and video databases conference

作者： Popescu, M Gader, P Univ Missouri Med Informat Grp Columbia MO 65201 USA

ISBN: (纸本)0819431273

A novel similarity measure based on the Choquet integral was introduced for retrieving images from a image database that "mostly" fit the query image. We showed that in certain conditions the measure is a norm, a fact that can be used to reduce the searching time using the triangle inequality. To test the new measure, a content based image retrieval system was built. The system was benchmarked against the visual retrieval cartridge, virage, built into Oracle 8 database system. The results suggested that the new measure is useful for image retrieval.

关键词： image database Choquet integral similarity measure OWA Oracle 8

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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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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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Rotation, translation, and scaling invariant color image indexing

Rotation, translation, and scaling invariant color image ind...

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7th storage and retrieval for image and video databases conference

作者： Celenk, M Shao, Y Ohio Univ Sch Elect Engn & Comp Sci Athens OH 45701 USA

ISBN: (纸本)0819431273

This paper describes a rotation, translation, and scaling (RTS) invariant color image indexing technique for imaging database systems. The features used for image indexing are color based, which are extracted using the principal component analysis, Hotelling transform, and moment invariants. This synthesized feature extraction technique is devised to be computationally efficient for on-line fast image storage and retrieval using color information Since the database indexing relies on a the use of average (mean) color vector and seven moment invariants of an image, the index storage requirement of the method is only a ten-dimensional (10-D) vector. This index storage efficiency is very desirable for many imaging database applications. A new similarity measure is also proposed based on the Tanimoto measure of recognizing similar patterns for fast image retrieval in large database systems. The underlying similarity measure is computationally effective since the vector inner product is the only operation needed for its computation. Four databases are experimented in the computer simulation of the algorithm to demonstrate the RTS property of the image retrieval. It is determined experimentally that the proposed method is not affected by substantial changes in the database images due to rotation, translation, and scaling. This is attributed to the fact that the moment features used for retrieval are not predefined sets;rather, they are obtained directly from the images submitted for recording or searching. This makes the algorithm very robust and attractive for many applications of the image storage and retrieval systems.

关键词： color image storage and retrieval principal components Hotelling transform moment invariants Tanimoto measure

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