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A pedestrian recognition method based on dynamic occlusion samples

A pedestrian re-identification, pedestrian technology, applied in character and pattern recognition, instruments, computer parts and other directions, can solve the problem of not improving the performance of occlusion samples, pedestrian images can not match the dynamic model state, etc., to improve generalization performance, The effect of improving the accuracy

Active Publication Date: 2019-02-19
TIANJIN NORMAL UNIVERSITY
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the technical problem that the occluded pedestrian image cannot match the dynamic model state and does not improve the performance of occluded samples. Therefore, the present invention provides a pedestrian re-identification method based on dynamic occluded samples

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  • A pedestrian recognition method based on dynamic occlusion samples
  • A pedestrian recognition method based on dynamic occlusion samples
  • A pedestrian recognition method based on dynamic occlusion samples

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Embodiment Construction

[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 1 is a flow chart of a method for pedestrian re-identification based on dynamic occlusion samples according to an embodiment of the present invention. figure 1As an example to illustrate some specific implementation processes of the present invention, such as figure 1 As shown, the described pedestrian re-identification method based on dynamic occlusion samples comprises the following steps:

[0048] Step...

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Abstract

The embodiment of the invention discloses a pedestrian recognition method based on dynamic occlusion samples. The method comprises: constructing an original image feature learning network framework; inputting a pedestrian image of a training set to obtain n local features, and learning and optimizing the local features, serially connecting the obtained n optimized local features as the original image features of the training pedestrian image; building the generator; generating an occluded pedestrian image; inputting the occluded pedestrian image into the generator to obtain n local features, and learning and optimizing the local features, serially connecting the obtained n local features as occluded image features; obtaining the final features of the training pedestrian image by using theoriginal image features and the occlusion image features, and performing pedestrian recognition by using the final features of the training pedestrian image. The invention makes full use of the advantages of the convolution neural network, learns the original image feature and the occlusion image feature of the pedestrian, and finally fuses the two features to represent the pedestrian image, thereby further improving the matching accuracy of the pedestrian recognition.

Description

technical field [0001] The invention belongs to the fields of pattern recognition and artificial intelligence, and in particular relates to a pedestrian re-identification method based on dynamic occlusion samples. Background technique [0002] Person Re-Identification (Person Re-Identification) mainly studies the method of searching for the same pedestrian under different cameras. This technology can quickly and accurately locate target pedestrians, so it has been widely used in security defense and other fields. However, due to the large changes in pedestrian posture, clothing, lighting and camera angles in real scenes, and pedestrians are often blocked by obstacles, these make pedestrian re-identification technology face huge challenges. [0003] In recent years, researchers have made great progress after applying deep learning methods to the field of pedestrian re-identification, which has greatly improved the correct search rate of pedestrian re-identification. In orde...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/103G06F18/2413
Inventor 张重司统振刘爽
Owner TIANJIN NORMAL UNIVERSITY
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