| Discriminative region extraction and feature selection based on the combination of SURF and saliency | |
| Deng Li; Wang Chunhong; Rao Changhui | |
| Volume | 8193 |
| 2011 | |
| Language | 英语 |
| Indexed By | Ei |
| Subtype | 会议论文 |
| Abstract | 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.; 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 Name | Proceedings 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 Date | 2011 |
| Document Type | 会议论文 |
| Identifier | http://ir.ioe.ac.cn/handle/181551/7761 |
| Collection | 自适应光学技术研究室（八室） |
| Corresponding Author | Deng 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. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| 2011-08-013.pdf（719KB） | 会议论文 | 开放获取 | CC BY-NC-SA | Application Full Text | ||
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