Compressed sensing ensemble classifier for human detection
文献类型：会议论文
| 作者 | Baochang Zhang; Juan Liu; Yongsheng Gao; Jianzhuang Liu |
| 出版日期 | 2013 |
| 会议名称 | 4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013 |
| 会议地点 | Beijing, China |
| 英文摘要 | This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major contributions of this paper are: 1) a novel principled framework for ensemble classifier design based on compressed sensing; 2) a new concept of considering both the simplicity of ensemble classifier and irrelevance of base classifiers towards optimal classifier design; and 3) a quadratic function for CSEC optimization which includes a new optimizable positive semi-definite relevance matrix to simultaneously select appropriate base classifiers with minimized relevance. Experimental results on INRIA and SDL databases show that the performance of CSEC is better than two most popular classifiers SVM and AdaBoost, as well as a most recent method CLML. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/4484]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2013 |
| 推荐引用方式 GB/T 7714 | Baochang Zhang,Juan Liu,Yongsheng Gao,et al. Compressed sensing ensemble classifier for human detection[C]. 见:4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013. Beijing, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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