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

Christopher F. Barnes

doi:10.1117/12.263149

6 January 1997 Object detection with a nearest-neighbor classifier based on residual vector quantization

Christopher F. Barnes

Proceedings Volume 2933, Terrorism and Counter-Terrorism Methods and Technologies; (1997) https://doi.org/10.1117/12.263149
Event: Enabling Technologies for Law Enforcement and Security, 1996, Boston, MA, United States

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.

Citation Download Citation

Christopher F. Barnes "Object detection with a nearest-neighbor classifier based on residual vector quantization", Proc. SPIE 2933, Terrorism and Counter-Terrorism Methods and Technologies, (6 January 1997); https://doi.org/10.1117/12.263149

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