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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hong Han Minglei Tong |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Electron. Eng., Xidian Univ., Xi'an, China (Hong Han) || Sch. of Electron. & Inf. Eng., Shanghai Univ. of Electr. Power, Shanghai, China (Minglei Tong) |
| Abstract | Different from most of the previous work, we detect motion human by region segmentation and classification through machine learning. In our method, based on optical flow, region segmentation is carried firstly and then, based on geometric flow, Bandelet transform is used to do feature extraction and classification. Some treatments were carried after optical flow field computation to denoising and some improvements in Bandelet transform were used to reduce time cost of feature extraction. The results of motion human detection experiments indicate that the proposed method can segment motion region more clearly and improve the performance of classifier effectively. It can be used to do real-time motion human detection in videos. |
| Starting Page | 459 |
| Ending Page | 464 |
| File Size | 599309 |
| Page Count | 6 |
| File Format | |
| ISBN | 9780769550503 |
| DOI | 10.1109/ICIG.2013.96 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-07-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Integrated optics Computer vision Image motion analysis spare representation human detection Transforms Optical imaging Feature extraction optical flow geometric flow Optical noise |
| Content Type | Text |
| Resource Type | Article |
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