Multimedia data is generally stored in compressed form in order to efficiently utilize the available storage facilities. Access to archives is dependent on our ability to browse compressed multimedia information - ret...
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Multimedia data is generally stored in compressed form in order to efficiently utilize the available storage facilities. Access to archives is dependent on our ability to browse compressed multimedia information - retrieval and tracking from coded videodatabases. In this paper, a novel visual search engine for videoretrieval and tracking from compressed multimedia databases is proposed. The goal of the project is the implementation of a visual browser that operates in a distributed environment where users initiate video searches and retrieve relevant video information simultaneously from multiple video archives. Being presented with a query in the form of template images of objects, the system operates on the compressed video to find the images or video sequences where those objects are present and their positions in the image. Upon user's request, the system will decompress and display only the video sequences of interest.
databases are increasingly being used to store multimedia objects such as maps, images, audio, and video. storage and retrieval of these objects is accomplished using multidimensional index structures such as R*-trees...
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databases are increasingly being used to store multimedia objects such as maps, images, audio, and video. storage and retrieval of these objects is accomplished using multidimensional index structures such as R*-trees and SS-trees. As dimensionality increases, query performance in these index structures degrades. This phenomenon, generally referred to as the dimensionality curse, can be circumvented by reducing the dimensionality of the data. Such a reduction is, however, accompanied by a loss of precision of query results. Current techniques such as QBIC use SVD transform-based dimensionality reduction to ensure high query precision. The drawback of this approach is that SVD is expensive to compute and, therefore, not readily applicable to dynamic databases. In this paper, we propose novel techniques for performing SVD-based dimensionality reduction in dynamic databases. When the data distribution changes considerably so as to degrade query precision, we recompute the SVD transform and incorporate it in the existing index structure. For recomputing the SVD-transform, we propose a novel technique that uses aggregate data from the existing index rather than the entire data. This technique reduces the SVD-computation time without compromising query precision. We then explore efficient ways to incorporate the recomputed SVD-transform in the existing index structure. These techniques reduce the computation time by a factor of 20 in experiments on color and texture image vectors. The error due to approximate computation of SVD is less than 10%. (C) 1999 Academic Press.
Illumination invariance is of paramount importance to annotate video sequences stored in large videodatabases consistently. Yet, popular texture analysis methods such as multichannel filtering techniques do not yield ...
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Illumination invariance is of paramount importance to annotate video sequences stored in large videodatabases consistently. Yet, popular texture analysis methods such as multichannel filtering techniques do not yield illumination-invariant texture representations. In this paper, we assess the effectiveness of three illumination normalisation schemes for texture representations derived from Gabor filter outputs. The schemes aim at overcoming intensity scaling effects due to changes in ilumination conditions. A theoretical analysis and experimental results enable us to select one scheme as the most promising one. In this scheme, a normalising factor is derived at each pixel by combining the energy responses of different filters at that pixel. The scheme overcomes illumination variations well, while still preserving discriminatory textural information. Further statistical analysis may shed light on other interesting properties or limitations of the scheme.
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 ...
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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.
This paper presents a simple and effective pre-processing method developed for the segmentation of MPEG compressed video sequences. The proposed method for scene-cut detection only involves computing the number of bit...
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This paper presents a simple and effective pre-processing method developed for the segmentation of MPEG compressed video sequences. The proposed method for scene-cut detection only involves computing the number of bits spent for each frame (encoding cost data), thus avoiding decoding the bitstream. The information is separated into I-, P-, B-frames, thus forming 3 vectors which are independently processed by a new peak detection algorithm based on overcomplete filter banks and on joint thresholding using a confidence number. Each processed vector yields a set of candidate frame numbers, i.e. 'hints' of positions where scene-cuts may have occurred. The 'hints' for all frame types are recombined into one frame sequence and clustered into scene cuts. The algorithm was not designed to distintuish among types of cuts but rather to indicate its position and duration. Experimental results show that the proposed algorithm is effective in detecting abrupt scene changes as well as gradual transitions. For precision demanding applications, the algorithm can be used with a low confidence factor just to select the frames that are worth being investigated by a more complex algorithm. The algorithm is not particularly tailored to MPEG and can be applied to most video compression techniques.
A scheme that reduces the needed storage considerably without reducing the retrieval effectiveness of a content-based imageretrieval (CBIR) system such as ASSERT is introduced. This scheme enables ASSERT to retrieve ...
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A scheme that reduces the needed storage considerably without reducing the retrieval effectiveness of a content-based imageretrieval (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.
The aim of this report is to be controversial and to engage a debate within the research community. Issues of whether some of the work in image and videodatabases has been directed at solutions in search of a problem...
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The aim of this report is to be controversial and to engage a debate within the research community. Issues of whether some of the work in image and videodatabases has been directed at solutions in search of a problem are discussed. Important applications in the area of media-based digital libraries that will enhance human experience are also detailed.
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 t...
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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.
This paper addresses the problem of recovering the semantic structure of broadcast news. A hierarchy of retrievable units is automatically constructed by integrating information from different media. The hierarchy pro...
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This paper addresses the problem of recovering the semantic structure of broadcast news. A hierarchy of retrievable units is automatically constructed by integrating information from different media. The hierarchy provides a compact yet meaningful abstraction of the broadcast news data similar to a conventional table of content that can serve as an effective index table, facilitating the capability of browsing through large amounts of data in a non-linear fashion. The recovery of the semantic structure of the data further enables the automated solutions in constructing visual representations that are relevant to the semantics as well as in establishing useful relationships among data units such as topic categorization and content based multimedia hyperlinking. Preliminary experiments of integrating different media for hierarchical segmentation of semantics have yielded encouraging results. Some of the results are presented and discussed in this paper.
A highly integrated wavelet-based image management system is proposed. Three solutions for key aspect of image management are derived: content-based imageretrieval (CBIR);image compression/decompression;and image tra...
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A highly integrated wavelet-based image management system is proposed. Three solutions for key aspect of image management are derived: content-based imageretrieval (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.
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