%0 Journal Article %A SHAN Zhaochen %A HUANG Dandan %A GENG Zhenye %A LIU Zhi %T Pedestrian Multi-Object Tracking Algorithm of Anchor-Free Detection %D 2022 %R 10.3778/j.issn.1002-8331.2011-0050 %J Computer Engineering and Applications %P 145-152 %V 58 %N 10 %X A multi-object tracking algorithm based on anchor-free detection is proposed to solve the problems of incorrect data correlation and poor tracking real-time due to detector omission and frequent occlusion in complex environment. The algorithm uses the method of predicting the thermal diagram of the target center to realize the target detection and location, and improves the problem of missing detection caused by the ambiguity of anchor frame regression. At the same time, the depth apparent feature extraction branch is embedded in the detection model, and the multi-task network of joint detection and tracking is built to improve the real-time performance. In order to solve the problem of data association error and track loss caused by occlusion of pedestrians in the tracking stage, a similarity measurement algorithm based on weighted multi-feature fusion is proposed to evaluate the matching degree of detection and tracking based on a variety of key features to significantly improve the accuracy of data association. A survival based tracking status update method is proposed to effectively recover lost track and improve tracking robustness. The tracking performance is tested on the MOT dataset. The experimental results show that the algorithm can effectively deal with occlusion and realize long-term stable tracking, taking into account both real-time and accuracy. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2011-0050