Object recognition based on spatial active basis template

Shaowu Peng; Jingcheng Xu

doi:10.1117/12.902012

2 December 2011 Object recognition based on spatial active basis template

Shaowu Peng, Jingcheng Xu

Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 80040V (2011) https://doi.org/10.1117/12.902012
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

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.

Citation Download Citation

Shaowu Peng and Jingcheng Xu "Object recognition based on spatial active basis template", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80040V (2 December 2011); https://doi.org/10.1117/12.902012

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KEYWORDS

Wavelets

Object recognition

Associative arrays

Image classification

Detection and tracking algorithms

Feature extraction

Image segmentation

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