Multi-categorical object recognition using method based on active contour basis model

doi:10.7523/j.issn.2095-6134.2009.4.011

Abstract

Abstract:

A new multi-categorical object recognition method based on the active contour basis model is proposed. The method builds a class-specific codebook of active contour bases, which is robust to scale variation and pose changes. Probabilistic learning by analyzing contextual information is performed using cascaded frame and boot strap dynamic sampling. A classifier is trained to determine the object categories and exact regions. Experimental results demonstrate that the proposed method achieves high efficiency in extracting manifold and complicated objects.

Key words: object recognition, contour basis, probabilistic learning, shape feature

CLC Number:

TP391

SUN Xian, HU Yan-Feng, WANG Hong-Qi. Multi-categorical object recognition using method based on active contour basis model[J]. , 2009, 26(4): 503-512.

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