Person re-identification method based on background suppression

Abstract

The invention discloses a person re-identification method based on background suppression. The method comprises the following steps: acquiring a plurality of image samples and extracting feature vectors, the extracting method comprises performing feature vector extraction on image blocks, and extracting HOG histogram feature vectors of the blocks at the same time; acquiring random fern features based on an HOG domain, performing background determination by adopting random fern features, and connecting the feature vectors of the image blocks to acquire the feature vectors of the image accordingto the result of the background determination; performing feature vector extraction on the to-be-identified image blocks, and connecting the feature vectors of the image blocks to acquire the featurevectors of the image; and calculating the similarity between the feature vectors of the to-be-identified image and the feature vectors of each image sample to obtain an identification result. According to the person re-identification method based on background suppression, the background determination is performed by adopting the random fern features based on the HOG domain, the background feature in the image is suppressed, the interference of background factors is reduced, and the accuracy of person re-identification is improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and more specifically relates to a pedestrian re-identification method based on background suppression. Background technique [0002] With the rapid development of society and the increasing progress of science, video surveillance systems appear in more and more occasions. The wide application of these monitoring systems brings a lot of convenience, but also brings certain problems. Because most of the current monitoring system is managed by humans, which is relatively boring and cannot respond in a timely manner. In order to solve this problem and give full play to the monitoring function of the camera, various intelligent monitoring systems are needed, using computer vision, machine learning, image processing and other knowledge, to automatically extract useful key information, and quickly and accurately locate the place where the abnormality occurs , and deal with it in a timely mann...

AI Technical Summary

Problems solved by technology

At present, there are mainly the following challenges in pedestrian re-identification: First, most of the image resolutions of current surveillance cameras are very low, which makes some very mature technologies such as face recognition unusable

Moreover, different cameras have different parameter configurations. Even the same camera will have different shooting effects due to different shooting angles.

The second is that the illumination changes, brightness changes, and angles do not change due to different external environments, and sometimes there are partial occlusions and noise interference.

However, because there are many backgrounds in the image to be recognized, it will interfere with the image features, resulting in poor recognition accuracy.

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