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《Journal of Dalian Minzu University》 2018-03
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Recursive False Positive Check Algorithm for Pedestrian Detection Based on Image Transformation

ZHANG Jing;YANG Da-wei;MAO Lin;School of Electromechanical Engineering,Dalian Minzu University;  
Due to the interference of complex environmental background,the efficiency of pedestrian detectors using HOG features has declined. To solve this problem,we propose a recursive false positive check algorithm for pedestrian detection based on image transformation. This algorithm makes the pedestrian detector become a recursive false positive check structure,through maintaining the construction of original pedestrian detector and utilizing the detection result as input image of pedestrian detector after image transformation. In order to reduce the false detection rate,image transformation methods such as size normalization,equalization and sharpening are adopted to check the results of pedestrian detector recursively. And fuzzy decision termination condition is introduced to achieve reasonable exit from iteration. The simulation results on INRIA and other collected datasets show that the method can remove the false detection results of the pedestrian detector and the correct detection rate is increased by 7. 6% compared with the original detection,which demonstrates the effectiveness of this method in the complex background conditions.
【Fund】: 国家自然科学基金资助项目(61673084);; 辽宁省自然科学基金资助项目(20170540192)
【CateGory Index】: TP391.41
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