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A Language for Content-Based Video Retrieval

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Abstract

We present an effective technique for automatic extraction, representation, and classification of digital video, and a visual language for formulation of queries to access the semantic information contained in digital video. We have devised an algorithm that extracts motion information from a video sequence. This algorithm provides a low-cost extension to the motion compensation component of the MPEG compression algorithm. In this paper, we present a visual language called VEVA for querying multimedia information in general, and video semantic information in particular. Unlike many other proposals that concentrate on browsing the data, VEVA offers a complete set of capabilities for specifying relationships between the image components and formulating queries that search for objects, their motions and their other associated characteristics. VEVA has been shown to be very expressive in this context mainly due to the fact that many types of multimedia information are inherently visual in nature.

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Authors
  1. Forouzan Golshani
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  2. Nevenka Dimitrova
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Golshani, F., Dimitrova, N. A Language for Content-Based Video Retrieval. Multimedia Tools and Applications 6, 289–312 (1998). https://doi.org/10.1023/A:1009612532460

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