Study on the Specified Target Traceability in Multi-camera

Cheng-feng ZHU, Dong YIN, Jin-wen DING, An Wang, Yu-hao LUO, Zhi-peng ZHOU, Ming-yue YUAN


In view of the tracing of the pedestrian history trajectory, a counter-tracking method based on multi-camera is proposed. Firstly, a basic database including many attributes such as video frame rate and perspective relationship is established. Secondly, all of the cameras in the environment are calibrated and the relationships among them are constructed. Various features obtained by ResNet neural network are used to improve the accuracy of recalibration for the processed camera data. Finally, using the mean-shift algorithm realizes target tracking and traceability in reverse-time. Compared with ASMS, ColorKCF and Staple algorithm, experiments in the paper show that the proposed method has some advantages in accuracy and loss rate of target tracking, which is effective in practical application.


Surveillance video, Target tracking, Neural network, Mean-shift


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