Xi'an Institute of Optics and Precision Mechanics,CAS
A universal pedestrian's foot-point and head-point recognition with improved motion detection algorithm | |
Shi, Liu1,2; Liu, Jiahang1; Yihao, Wang1 | |
2017 | |
会议名称 | 2nd International Conference on Image, Vision and Computing, ICIVC 2017 |
会议录名称 | 2017 2nd International Conference on Image, Vision and Computing, ICIVC 2017 |
页码 | 281-287 |
会议日期 | 2017-06-02 |
会议地点 | Chengdu, China |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
产权排序 | 1 |
摘要 | Detecting pedestrians' spatial locations is a key, yet challenging task in video surveillance. From video sequences, we can apply motion detection algorithm to detect the whole pedestrians, and recognize pedestrians' foot-point locations with foot-point recognition method. While we propose a solution to recognize pedestrians' head-point locations for partially occluded pedestrians in complex scenes. Then, a few simple mappings can be used for converting head-point to foot-point and converting 2-D locations to 3-D spatial locations in computer vision. In this paper, we present a pixel-level background sample set motion detection approach based on Self-Balanced SENsitivity SEgmenter, coined SuBSENSE algorithm. Instead of using the same background/foreground segmentation criterion for low and high brightness distribution areas, we use completely different segmentation criterion for low and high brightness, respectively. Besides, for an actual scenario with camouflaged foreground objects, simple color and texture feature could not detect these motion objects. To best address these disadvantages, we introduce normalized color feature and extended local binary similarity pattern (ELBSP) operator by adaptive threshold to segment motion objects for high brightness while providing normalized color feature by perception-inspired confidence interval for high brightness. Due to the diversity of camera gesture in video images, we can't directly gain foot-point and head-point location from the results of motion detection. For foot-point, principal component analysis is employed in getting pedestrian's upright direction and mapping the whole object to this direction. Moreover, color feature, area feature, and position feature are utilized for detecting head-point. Experiments show that it outperforms original motion detection approach and several state-of-the-art methods, and can accurately obtain pedestrians' 2-D locations in real scenarios. © 2017 IEEE. |
作者部门 | 遥感与智能信息系统研究中心 |
DOI | 10.1109/ICIVC.2017.7984562 |
收录类别 | EI ; ISTP |
ISBN号 | 9781509062379 |
语种 | 英语 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/29418 |
专题 | 遥感与智能信息系统研究中心 |
作者单位 | 1.Xi'An Institute of Optics and Precision Mechanics of CAS, China 2.University of Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Shi, Liu,Liu, Jiahang,Yihao, Wang. A universal pedestrian's foot-point and head-point recognition with improved motion detection algorithm[C]:Institute of Electrical and Electronics Engineers Inc.,2017:281-287. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
A universal pedestri(16909KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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