Pedestrian re-identification method based on human skeleton key point segmentation and column convolution

Abstract

The invention relates to a pedestrian re-identification method based on human skeleton key point segmentation and column convolution. The method comprises the following steps: (1) preparing a pedestrian data set; (2) sending the training set to a network A, obtaining upper body picture information and lower body picture information, wherein the upper body picture information refers to a high-dimensional matrix X containing pedestrian upper body information, and the lower body picture information refers to a high-dimensional matrix Y containing pedestrian lower body information; (3) sending thehigh-dimensional matrix X into a network B; (4) sending the high-dimensional matrix Y into a network C; and (5) verifying by using the test set, and performing result detection. According to the method, all parts of the human body can be distinguished more accurately based on region segmentation of the human skeleton key points, human body part alignment can be conducted more effectively, and therobustness of the model can be effectively improved. According to the invention, information can be transmitted between pixel rows in the image, and the target recognition rate is effectively improved.

Description

technical field [0001] The invention belongs to the field of pedestrian re-identification, in particular to a pedestrian re-identification method based on human skeleton key point segmentation and column convolution. Background technique [0002] Person Re-identification (Person Re-identification), also known as pedestrian re-identification, or ReID for short, is a technology that uses computer vision technology to determine whether a specific pedestrian exists in an image or video sequence, and is widely considered to be a sub-problem of image retrieval. Given a monitored pedestrian image, retrieve the pedestrian image across devices. In surveillance video, due to camera resolution and shooting angle, it is usually impossible to obtain very high-quality face pictures. When face recognition fails, pedestrian re-identification becomes a very important substitute technology. [0003] At present, the methods for realizing pedestrian re-identification include methods based on ...

AI Technical Summary

Problems solved by technology

[0009]Obviously, when the proportion of the human body in the input picture is different, because the human body structure information is not considered, the horizontal division will cause the area division to not correspond, resulting in erroneous Higher detection rate results

At the same time, the obvious spatial relationship of the lower body is not considered, and the features extracted by the horizontal convolution are not accurate enough, resulting in poor final recognition effect

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