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Proceedings Paper

Object recognition based on spatial active basis template
Author(s): Shaowu Peng; Jingcheng Xu
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Paper Abstract

This article presents a method for the object classification that combines a generative template and a discriminative classifier. The method is a variant of the support vector machine (SVM), which uses Multiple Kernel Learning (MKL). The features are extracted from a generative template so called Active Basis template. Before using them for object classification, we construct a visual vocabulary by clustering a set of training features according to their orientations. To keep the spatial information, a "spatial pyramid" is used. The strength of this approach is that it combines the rich information encoded in the generative template, the Active Basis, with the discriminative power of the SVM algorithm. We show promising results of experiments for images from the LHI dataset.

Paper Details

Date Published: 2 December 2011
PDF: 6 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040V (2 December 2011); doi: 10.1117/12.902012
Show Author Affiliations
Shaowu Peng, South China Univ. of Technology (China)
Jingcheng Xu, South China Univ. of Technology (China)


Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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