QQ客服 官方微博 反馈留言

	Camera Calibration from Periodic Motion of a Pedestrian
	Huang, Shiyao ; Ying, Xianghua ; Rong, Jiangpeng ; Shang, Zeyu ; Zha, Hongbin
	2016
英文摘要	Camera calibration directly from image sequences of a pedestrian without using any calibration object is a really challenging task and should be well solved in computer vision, especially in visual surveillance. In this paper, we propose a novel camera calibration method based on recovering the three orthogonal vanishing points (TOVPs), just using an image sequence of a pedestrian walking in a straight line, without any assumption of scenes or motions, e.g., control points with known 3D coordinates, parallel or perpendicular lines, non-natural or pre-designed special human motions, as often necessary in previous methods. The traces of shoes of a pedestrian carry more rich and easily detectable metric information than all other body parts in the periodic motion of a pedestrian, but such information is usually overlooked by previous work. In this paper, we employ the images of the toes of the shoes on the ground plane to determine the vanishing point corresponding to the walking direction, and then utilize harmonic conjugate properties in projective geometry to recover the vanishing point corresponding to the perpendicular direction of the walking direction in the horizontal plane and the vanishing point corresponding to the vertical direction. After recovering all of the TOVPs, the intrinsic and extrinsic parameters of the camera can be determined. Experiments on various scenes and viewing angles prove the feasibility and accuracy of the proposed method.; NNSFC [61322309, 61273283, 91120004]; CPCI-S(ISTP); 3025-3033
语种	英语
出处	29th IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
DOI标识	10.1109/CVPR.2016.330
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470254]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Huang, Shiyao,Ying, Xianghua,Rong, Jiangpeng,et al. Camera Calibration from Periodic Motion of a Pedestrian. 2016-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。