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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wen-Chang Cheng Ding-Mao Jhan |
| Copyright Year | 2011 |
| Description | Author affiliation: Dept. Computer Science and Information Eng, Chaoyang University of Technology, Taichung, Taiwan (Wen-Chang Cheng; Ding-Mao Jhan) |
| Abstract | In this paper, we improve cascade-Adaboost classifier and propose a cascade-Adaboost-SVM classifier. It is combined with Adaboost and SVM and real-time pedestrian detection system with a single camera. We capture the pedestrian candidate areas with a window of fixed size, conduct feature extraction to candidate areas and mobile images with Haar-like rectangle feature calculation and then, complete pedestrian by using the proposed cascade-Adaboost-SVM classifier. As this cascade-Adaboost-SVM classifier can adjust numbers of cascade classifiers adaptively, it can construct cascade classifiers effectively based on training set. Finally, we complete the pedestrian detection experiment with the database of captured samples and PETs database. The experimental result shows that the cascade classifier proposed by us can get better performance than cascade-Adaboost classifier and its accuracy can reach 99.5% and the false alarm rate is less than 1e-5. |
| Starting Page | 1430 |
| Ending Page | 1435 |
| File Size | 671653 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457706523 |
| ISSN | 1062922X |
| e-ISBN | 9781457706530 |
| DOI | 10.1109/ICSMC.2011.6083870 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Classification algorithms Feature extraction Cameras Databases Support vector machine classification Ensemble classifier Background subtraction Human detection Object recognition Haar-like feature |
| Content Type | Text |
| Resource Type | Article |
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