收稿日期: 2008-12-02
修回日期: 2009-04-10
网络出版日期: 2009-07-15
基金资助
国家自然科学基金(40871209)、国家863计划(2006AA12Z149)和中国科学院电子学研究所青年创新基金资助
Multi-categorical object recognition using method based on active contour basis model
Received date: 2008-12-02
Revised date: 2009-04-10
Online published: 2009-07-15
孙显 , 胡岩峰 , 王宏琦 . 基于主动式边界基元模型的多类目标识别方法[J]. 中国科学院大学学报, 2009 , 26(4) : 503 -512 . DOI: 10.7523/j.issn.2095-6134.2009.4.011
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
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