A robust system for real-time pedestrian detection and tracking  

作　　者：李琦 邵春福 赵熠 

机构地区：[1]Key Laboratory for Urban Transportation Complex Systems Theory and Technology of Ministry of Education(Beijing Jiaotong University)

出　　处：《Journal of Central South University》2014年第4期1643-1653,共11页中南大学学报（英文版）

基　　金：Project(50778015)supported by the National Natural Science Foundation of China;Project(2012CB725403)supported by the Major State Basic Research Development Program of China

摘　　要：A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules： video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.

关 键 词：image processing technique pedestrian detection tracking video camera 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]