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Proceedings Paper

Indexing of compressed video sequences
Author(s): Fayez M. Idris; Sethuraman Panchanathan
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Paper Abstract

In this paper, we propose an algorithm based on vector quantization (VQ) for indexing of video sequences in the compressed form. In VQ, the image to be compressed is decomposed into L-dimensional vectors. Each vector is mapped into one of a finite set of codewords (codebook). Vectors are encoded in the intraframe mode using adaptive VQ. Each frame is represented by a set of labels and a codebook. We note that the codebook reflects the contents of the frame being compressed and similar frames have similar codebooks. The labels are used for cut detection and to generate indices to store and retrieve video sequences. The proposed technique provides fast access to the sequences in the database. In addition, this technique combines video compression and video indexing. Simulation results confirm the substantial gains of the proposed technique in comparison with other techniques reported in the literature.

Paper Details

Date Published: 13 March 1996
PDF: 7 pages
Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); doi: 10.1117/12.234801
Show Author Affiliations
Fayez M. Idris, Univ. of Ottawa (Canada)
Sethuraman Panchanathan, Univ. of Ottawa (Canada)


Published in SPIE Proceedings Vol. 2670:
Storage and Retrieval for Still Image and Video Databases IV
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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