CASIA OpenIR  > 智能感知与计算研究中心
EDA Approach for Model Based Localization and Recognition of Vehicle
Zhaoxiang Zhang; Weishan Dong; Kaiqi Huang; Tieniu Tan
2007
Conference NameCVPR workshop on the Seventh International Workshop on Visual Surveillance
Source PublicationCVPR workshop on the Seventh International Workshop on Visual Surveillance
Pages1-8
Conference Date2007-06-01
Conference PlaceMinneapolis, Minnesota, USA
AbstractWe address the problem of model based recognition. Our aim is to localize and recognize road vehicles from monocular images in calibrated scenes. A deformable 3D geometric vehicle model with 12 parameters is set up as prior information and Bayesian Classification Error is adopted for evaluation of fitness between the model and images. Using a novel evolutionary computing method called EDA (Estimation of Distribution Algorithm), we can not only determine the 3D pose of the vehicle, but also obtain a 12 dimensional vector which corresponds to the 12 shape parameters of the model. By clustering obtained vectors in the parameter space, we can recognize different types of vehicles. Experimental results demonstrate the effectiveness of the approach to vehicles of different types and poses. Thanks to EDA, we can not only localize and recognize vehicles, but also show the whole evolution procedure of the deformable model which gradually fits the image better and better.
KeywordEvolutionary Computation   image Classification   image Recognition
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12726
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,Weishan Dong,Kaiqi Huang,et al. EDA Approach for Model Based Localization and Recognition of Vehicle[C],2007:1-8.
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