Crowdedness estimation approach based on stereovision for bus passengers  

作　　者：朱秋煜 江毅凭 邓伟俊 唐利 

机构地区：[1]School of Communication and Information Engineering,Shanghai University [2]Shanghai Transportation Investment Information Technology Company Limited

出　　处：《Journal of Shanghai University(English Edition)》2010年第1期17-23,共7页上海大学学报（英文版）

基　　金：supported by the Development Foundation of Shanghai Municipal Commission of Science and Technology (Grant No.072112007);the Shanghai Leading Acdemic Discipline Project (Grant No.J50104)

摘　　要：An estimation approach is proposed in this paper based on the binocular stereovision to collect the degree of crowdedness in public transports. The proposed method combines the disparity with frame differences to extract the foreground object. An adaptive window normalized cross correlation （NCC） matching and interpolated method is applied to get the sub-pixel image disparity value. Then, the foreground object is projected to the horizontal plane to eliminate the influence of the occlusion and perspective effect. Finally the degree of crowdedness is calculated from the area and the perimeter of the foreground objects. Experimental results show that the proposed method can obtain good estimation results in the simulated scenes in the laboratory and on parking or moving buses. This approach is effective to illumination changes, shadows and occlusion of passengers.An estimation approach is proposed in this paper based on the binocular stereovision to collect the degree of crowdedness in public transports. The proposed method combines the disparity with frame differences to extract the foreground object. An adaptive window normalized cross correlation （NCC） matching and interpolated method is applied to get the sub-pixel image disparity value. Then, the foreground object is projected to the horizontal plane to eliminate the influence of the occlusion and perspective effect. Finally the degree of crowdedness is calculated from the area and the perimeter of the foreground objects. Experimental results show that the proposed method can obtain good estimation results in the simulated scenes in the laboratory and on parking or moving buses. This approach is effective to illumination changes, shadows and occlusion of passengers.

关 键 词：PASSENGER degree of crowdedness binocular stereovision DISPARITY foreground object detection 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN911.7[自动化与计算机技术—计算机科学与技术]