A Pedestrian Re-Identification Method Based on Locally Embedded Deep Features
A local and pedestrian technology, applied in the field of artificial intelligence and computer vision, to achieve the effect of improving the accuracy rate
Active Publication Date: 2021-10-15
天津府易智能信息技术有限公司
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[0004] The purpose of the present invention is to solve the problem that the structural information provided by the local sub-region has a great influence on the pedestrian re-identification results. Therefore, the present invention provides a pedestrian re-identification method based on local embedded depth features
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[0046] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.
[0047] figure 1It is a flow chart of a pedestrian re-identification method based on local embedded depth features according to an embodiment of the present invention, as follows figure 1 Some specific implementation processes of the present invention are described by way of example. The method of the present invention is a pedestrian re-identification method based on local embedded depth features, and its specific steps...
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The embodiment of the present invention discloses a pedestrian re-identification method based on local embedded depth features, the method includes: constructing a verification network and a recognition network; training the verification network, extracting the local feature map of the training image to obtain its overall summed feature map; using The overall summation feature map is used to train the recognition network; the verification network is used to obtain the overall summation feature map of the image to be recognized and the test image and use it as the input of the recognition network, and the image to be recognized and the test image are extracted in the fully connected layer of the recognition network The feature vector of the image to be recognized; the recognition result of the image to be recognized is obtained by calculating the distance between the image to be recognized and the feature vector of the test image. The present invention uses the verification network to map the local features to the same space, so that similar pedestrian images are closer and non-similar pedestrian images are farther away, and the recognition network is used to learn features with complete structural information and stronger discrimination, so that Improve the accuracy of pedestrian re-identification matching.
Description
technical field [0001] The invention belongs to the technical fields of computer vision and artificial intelligence, and in particular relates to a pedestrian re-identification method based on local embedded depth features. Background technique [0002] Pedestrian re-identification (Re-identification) refers to given a pedestrian image, identifying the same image as the person in the pedestrian image library of the scene captured by multiple cameras. As people pay more and more attention to public safety, video surveillance systems are widely used in public safety places. It is becoming more and more difficult to observe and process massive surveillance images manually. Pedestrian re-identification as an application The technology of quickly matching pedestrians by computer can replace manual operation to a large extent, so it has been widely studied. Due to the differences between different camera equipment, and the appearance of pedestrians is easily affected by factors s...
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IPC IPC(8): G06K9/00G06K9/46G06N3/06G06N3/08
CPCG06N3/06G06N3/084G06V40/10G06V10/44
Inventor 张重黄美艳刘爽
Owner 天津府易智能信息技术有限公司