Pedestrian target tracking method based on depth learning
A pedestrian target and deep learning technology, applied in image analysis, image enhancement, instruments, etc., can solve the problems of training sample pollution, feature pertinence is not strong, and cannot be directly applied to usage scenarios, so as to improve accuracy and efficiency Effect
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[0135] In order to prove that the pedestrian target tracking method based on deep learning has advantages in performance and efficiency, the present invention conducts verification and analysis through the following experiments.
[0136] A. Experimental data
[0137] The present invention conducts experiments on the MOT-16 data set, which contains 14 video sequences.
[0138] B. Experimental platform
[0139] Hardware: CPU Intel Xeon E5-2650v3, memory 64G, GPU GeForce GTX TITANX, video memory 12G, hard disk 4TB 7200 rpm.
[0140] Software: operating system windows8, Ubuntu16.04, experimental platform Caffe, MatconvNet, Matlab.
[0141] C Pedestrian Object Tracking Evaluation Criteria
[0142] Mean Overlap Precision (mOP), Speed Evaluation Standard FPS, Average Tracking Time.
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