We describe a system for browsing and interactively retrieving video sequences over the Internet at multiple spatial and temporal resolutions. Each video sequence is decomposed into a hierarchy of video view elements ...
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ISBN:
(纸本)0819429880
We describe a system for browsing and interactively retrieving video sequences over the Internet at multiple spatial and temporal resolutions. Each video sequence is decomposed into a hierarchy of video view elements that are retrieved in a progressive fashion. The client browser builds the views of the video sequence by retrieving, caching and assembling the view elements, as needed. This allows the user to quickly browse the video over the Internet by starting with a coarse, low-resolution view and by selectively zooming-in along the temporal and spatial dimensions. We demonstrate that the video view element method is able to represent and deliver the video in a compact form while significantly speeding up the access and progressive retrieval over the Internet.
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 no...
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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 imageretrieval 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 imageretrieval.
image histogram is an image feature widely used in content-based imageretrieval and video segmentation. It is simple to compute yet very effective as a feature in detecting image-to-image similarity, or frame-to-fram...
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ISBN:
(纸本)0819431273
image histogram is an image feature widely used in content-based imageretrieval 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 imageretrieval and video shot segmentation.
imageretrieval 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 in...
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ISBN:
(纸本)0819431273
imageretrieval 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.
This paper investigates clustering techniques as a method of organizing imagedatabases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglom...
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ISBN:
(纸本)0819429880
This paper investigates clustering techniques as a method of organizing imagedatabases to support popular visual management functions such as searching, browsing and navigation. Different types of hierarchical agglomerative clustering techniques are studied as a method of organizing features spaces as well as summarizing image groups by the selection of a few appropriate representatives. retrieval performance using both single and multiple level hierarchies are experimented with and the algorithms show an interesting relationship between the top k correct retrievals and the number of comparisons required. Some arguments are given to support the use of such cluster-based techniques for managing distributed imagedatabases.
Many content-based methods have been proposed to retrieve images from multimedia databases. Current index structures, such as R*-tree, SS-tree and SS+-tree, have a large overlapping area among their nodes, especially ...
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ISBN:
(纸本)0819429880
Many content-based methods have been proposed to retrieve images from multimedia databases. Current index structures, such as R*-tree, SS-tree and SS+-tree, have a large overlapping area among their nodes, especially at the high level of the indexing tree. The overlapping area causes the search engine to compare a large number of nodes and hence, it is very inefficient to retrieve at very high levels of the index tree. We present a scheme to combine browsing with retrieval in searching for images. The browser uses the content-based index structure of imagedatabases. It provides users with a visual tool to narrow the search quickly to a small region and to avoid a large number of comparisons. Combined with retrieval, it produces a very efficient content-based retrieval method.
Intelligent access to multimedia databases for "naive user" should probably be based on queries formulation by "intelligent agents". These agents should "understand" the semantics of the ...
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ISBN:
(纸本)0819429880
Intelligent access to multimedia databases for "naive user" should probably be based on queries formulation by "intelligent agents". These agents should "understand" the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios. In our project we have developed a method for image segmentation into semantic objects, even in the case of still images. We use this method, and user-defined collections of such objects, and to characterize stories contents. For this purpose, we also use audio information from selected parts of the video. Stories are characterized by a set of visual concepts and words, and semantic similarity between stories is evaluated based on information retrieval methods. The system learns user preferences, and incrementally builds a user profile, which is used to present relevant stories in appropriate order. This approach was used to build a mockup of a simple "plus" engine, which is presently being experimented.
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 th...
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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 imagestorage 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 imageretrieval 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 imageretrieval. 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 imagestorage and retrieval systems.
The color histogram of an image has been widely used as a feature descriptor for the image in content-based retrieval applications. In this paper, some results from our investigation efforts into the usage are reporte...
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ISBN:
(纸本)0819431273
The color histogram of an image has been widely used as a feature descriptor for the image in content-based retrieval applications. In this paper, some results from our investigation efforts into the usage are reported. We outline three typical color space quantization schemes used in our experiments and introduce the soft-decision histogramming method to eliminate the discontinuity problem in traditional color histogram population process. Then, to improve the effectiveness of color histogram based retrieval algorithms, several similarity metrics are proposed for comparing color histograms, including three special forms of the Kantorovich metric.
This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of field...
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ISBN:
(纸本)0819431273
This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of fields, and there are many issues that are still waiting a satisfactory solution. In this paper we present our (albeit still partial) answer to some of these problems, and the future directions of our work. Our design is divided in two layers: a Logbook which operates as a short time repository of unsummarized and unprocessed data, and a long term spatio-temporal database which stores and queries sumamrized data.
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