Pedestrian re-identification algorithm implementation method based on HSV and SDALF

A pedestrian re-identification and implementation method technology, which is applied in the field of pedestrian re-identification algorithm based on HSV and SDALF, can solve the problems of poor pedestrian feature extraction and low pedestrian re-identification accuracy, and achieve the effect of improving accuracy

Active Publication Date: 2018-02-09
ZHEJIANG NORMAL UNIVERSITY
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Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a pedestrian re-identification algorithm implementation method based on HSV and SDAL

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  • Pedestrian re-identification algorithm implementation method based on HSV and SDALF
  • Pedestrian re-identification algorithm implementation method based on HSV and SDALF
  • Pedestrian re-identification algorithm implementation method based on HSV and SDALF

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Embodiment 1

[0047] Extract the R, G, and B values ​​of each pixel in the picture a, and use V=max(R, G, B), Convert the pedestrian picture a represented by RGB to a picture represented by HSV. The optimized Graph Cut algorithm is used to extract multi-dimensional feature vectors from the converted image a, and a logistic regression is used to find an optimal classification surface to distinguish pedestrian targets from background and block pedestrian targets. The HSV histogram is calculated with the spatial distribution coverage operator and the color bilateral operator, and the pedestrian feature descriptor is obtained as

[0048]

[0049] A i Indicates the i-th image in the pedestrian image library A, H hsv is the HSV color histogram, n is the number of body sub-blocks, according to the division, n=5.

[0050] Let a and A 1 That is, the first picture in the A database matches the left half of the upper body. There are n pixels in the left half of the upper body in picture a, and...

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Abstract

The invention discloses a pedestrian re-identification algorithm implementation method based on HSV and SDF. The method comprises the following steps of acquiring pedestrian video data with a camera;extracting the moving object by using the discrete fourier and local frequency domain features, and generating a pedestrian picture library; selecting a pedestrian picture from the pedestrian picturelibrary, converting the RGB three-channel picture into a picture represented by an HSV color space; distinguishing the pedestrian target and the background through a Graph Cut algorithm, and blockingthe pedestrian targets; calculating the HSV histogram by adopting a spatial distribution coverage operator and a color bilateral operator, obtaining a pedestrian feature descriptor, and calculating the similarity of the pictures by using Euclidean distance; and sorting the pedestrian pictures in the pedestrian picture library with a penalty function and outputting the first six pedestrian picturesto obtain the final result set of pedestrian detection. The method can effectively solve the problem of low detection precision existing in the current pedestrian re-identification, has the advantages of clear algorithm, easy understanding and high pedestrian re-identification precision.

Description

technical field [0001] The invention belongs to the field of image retrieval, in particular to a method for realizing a pedestrian re-identification algorithm based on HSV and SDALF. Background technique [0002] Pedestrian re-identification refers to the technology of using computer vision technology to judge whether there is a specific pedestrian in the image sequence. Pedestrian re-identification technology is mainly used in video surveillance and image retrieval. In criminal investigation work, criminal investigators often have to browse the videos of multiple cameras to find out which cameras a specific pedestrian has appeared in. [0003] At present, there are many methods for pedestrian re-identification. For example, the Chinese invention patent with the patent number CN201611199109.8 discloses a pedestrian re-identification method and system based on deep learning and reinforcement learning. The pedestrian re-identification method and system include pedestrian iden...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/103G06V20/40G06V20/46G06V10/56G06V2201/07G06F18/22
Inventor 张克华田林晓朱苗苗金伦马佳航廖明
Owner ZHEJIANG NORMAL UNIVERSITY
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