CASIA OpenIR  > 智能感知与计算研究中心
3D Model Based Vehicle Tracking by Optimizing Gradient Based Fitness Evaluation
Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan; Yunhong Wang
2010
Conference NameICPR2010
Source PublicationICPR2010
Pages1771-1774
Conference Date2010
Conference PlaceIstanbul, Turkey
AbstractWe address the problem of 3D model based vehicle tracking from monocular videos of calibrated traffic scenes. A 3D wire-frame model is set up as prior information and an efficient fitness evaluation method based on image gradients is introduced to estimate the fitness score between the projection of vehicle model and image data, which is then combined into a particle filter based framework for robust vehicle tracking. Numerous experiments are conducted and experimental results demonstrate the effectiveness of our approach for accurate vehicle tracking and robustness to noise and occlusions.
KeywordGradient Methods   object Detection   particle Filtering 
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12700
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
First Author Affilication中国科学院自动化研究所
Corresponding Author Affilication中国科学院自动化研究所
Recommended Citation
GB/T 7714
Zhaoxiang Zhang,Kaiqi Huang,Tieniu Tan,et al. 3D Model Based Vehicle Tracking by Optimizing Gradient Based Fitness Evaluation[C],2010:1771-1774.
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