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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yea-Shuan Huang Zhi-Hong Ou Hsiang-Wen Hsieh Hung-Hsiu Yu |
| Copyright Year | 2011 |
| Description | Author affiliation: Mechanical and System Laboratory, Industrial Technology Research Institute, Hsinchu, Taiwan (Hsiang-Wen Hsieh; Hung-Hsiu Yu) || Dept. of Computer Science and Information Engineering, Chung-Hua University, Hsinchu, Taiwan (Yea-Shuan Huang; Zhi-Hong Ou) |
| Abstract | This paper presents a moving object detection method based on texture information extracted from images. Every image captured from the camera is converted into Local Binary Pattern (LBP). Salient feature points extracted from previous LBP are compared with those features found from the current LBP with a block matching approach so that the corresponding feature points from the successive image frames can be identified. If multiple correspondences exist between feature points, the motion vectors of each feature points are then calculated to determine the best corresponding features on the current LBP. Finally, with clustering of motion vectors, all the moving objects on image frames can be successfully detected and identified. Experimental results show that the average matching accuracy rate is 95.12%, and the average processing time for moving object detection is 46.2ms. |
| Starting Page | 1205 |
| Ending Page | 1209 |
| File Size | 828011 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781612844879 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-15 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Asian Control Association |
| Subject Keyword | Computer vision Image motion analysis motion vector Tracking feature point detection object segmentation Object detection Feature extraction Optical imaging clustering Pixel Block matching |
| Content Type | Text |
| Resource Type | Article |
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