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Discriminative region extraction and feature selection based on the combination of SURF and saliency
Deng Li; Wang Chunhong; Rao Changhui
Volume8193
2011
Language英语
Indexed ByEi
Subtype会议论文
AbstractThe objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.; The objective of this paper is to provide a possible optimization on salient region algorithm, which is extensively used in recognizing and learning object categories. Salient region algorithm owns the superiority of intra-class tolerance, global score of features and automatically prominent scale selection under certain range. However, the major limitation behaves on performance, and that is what we attempt to improve. By reducing the number of pixels involved in saliency calculation, it can be accelerated. We use interest points detected by fast-Hessian, the detector of SURF, as the candidate feature for saliency operation, rather than the whole set in image. This implementation is thereby called Saliency based Optimization over SURF (SOSU for short). Experiment shows that bringing in of such a fast detector significantly speeds up the algorithm. Meanwhile, Robustness of intra-class diversity ensures object recognition accuracy.
Conference NameProceedings of SPIE - The International Society for Optical Engineering, v 8193, 2011, International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications
Conference Date2011
Document Type会议论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/7761
Collection自适应光学技术研究室(八室)
Corresponding AuthorDeng Li
Affiliation中国科学院光电技术研究所
Recommended Citation
GB/T 7714
Deng Li,Wang Chunhong,Rao Changhui. Discriminative region extraction and feature selection based on the combination of SURF and saliency[C],2011.
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