Improved DeepSort target detection tracking method based on YOLOv4
A target detection and detection frame technology, applied in the field of computer vision, can solve the problems of poor target tracking effect, achieve good tracking effect, reduce missed detection, and improve robustness
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[0024] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0025] see Figure 1 to Figure 4 , the present invention provides an improved DeepSort target detection and tracking method based on YOLOv4, comprising:
[0026] S101 input data to obtain the detection frame of the current frame;
[0027] After the data is input, it is detected by the YOLOv4 algorithm to obtain the depth features of the detection frame and image;
[0028] The specific steps are:
[0029] S201 input target picture;
[0030] S202 performs an undistorted operation on the target image, and normalizes it, and inpu...
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