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Proceedings Paper

Object detection with a nearest-neighbor classifier based on residual vector quantization
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Paper Abstract

The use of residual (multiple stage) vector quantizer codevectors in a nearest neighbor classifier for direct classification of image pixel data is proposed. This approach combines the successive approximation process generated by the residual vector quantizer with sequential decision making. This approach potentially has the advantage of making large data base searches for small object or texture recognition in images both computation and memory efficient.

Paper Details

Date Published: 6 January 1997
PDF: 9 pages
Proc. SPIE 2933, Terrorism and Counter-Terrorism Methods and Technologies, (6 January 1997); doi: 10.1117/12.263149
Show Author Affiliations
Christopher F. Barnes, Georgia Institute of Technology (United States)

Published in SPIE Proceedings Vol. 2933:
Terrorism and Counter-Terrorism Methods and Technologies
Wade Ishimoto, Editor(s)

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