Robust vehicle registration method based on 3D model for traffic
Zheng, Yuan; Peng, Silong,
2013
发表期刊International Journal of Signal Processing, Image Processing and Pattern Recognition,
卷号6(5)期号:2013年06期页码:pp 129-142 (EI, SCI)
摘要3D-2D vehicle registration provides a new way for vehicle recognition, localization and tracking in traffic surveillance systems. In this paper we present two novel fitness functions to measure 3D-2D vehicle matching, where 3D wire-frame model is used. Unlike the existing vehicle registration methods, we group the model's wireframes into the important and unimportant ones in view of the disaccord between real vehicle and the wire-frame model. The important wireframes generally well fit the corresponding image edges, whereas the image edges corresponding to the unimportant wireframes may not exist due to the streamlined design of real vehicle. For more accurate matching, the fitting of the important wireframes is underlined in both two fitness functions. In the first fitness function, the larger weight coefficient is assigned to the fitting of the important wireframes; in the second fitness function, two different functions are used for the fitting of the model's wireframes instead of two different weight coefficients. Experiments on real traffic videos verify the correctness and robustness of the proposed fitness functions
关键词3d-2d Matching Wire-frame Model Local Image Gradient Traffic Surveillance
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12960
专题智能制造技术与系统研究中心_多维数据分析
通讯作者Zheng, Yuan
推荐引用方式
GB/T 7714
Zheng, Yuan,Peng, Silong,. Robust vehicle registration method based on 3D model for traffic[J]. International Journal of Signal Processing, Image Processing and Pattern Recognition,,2013,6(5)(2013年06期):pp 129-142 (EI, SCI).
APA Zheng, Yuan,&Peng, Silong,.(2013).Robust vehicle registration method based on 3D model for traffic.International Journal of Signal Processing, Image Processing and Pattern Recognition,,6(5)(2013年06期),pp 129-142 (EI, SCI).
MLA Zheng, Yuan,et al."Robust vehicle registration method based on 3D model for traffic".International Journal of Signal Processing, Image Processing and Pattern Recognition, 6(5).2013年06期(2013):pp 129-142 (EI, SCI).
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