Pedestrian re-identification method based on attribute feature and weighted block feature fusion

A pedestrian re-identification and attribute feature technology, which is applied in the field of pedestrian re-identification combined with block features, can solve the problem of low pedestrian re-identification accuracy, achieve good pedestrian re-identification results, improve matching accuracy, and high discrimination and the effect of robustness

Active Publication Date: 2019-04-16
ACADEMY OF BROADCASTING SCI STATE ADMINISTATION OF PRESS PUBLICATION RADIO FILM & TELEVISION +1
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AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art, propose a pedestrian re-identification meth

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  • Pedestrian re-identification method based on attribute feature and weighted block feature fusion
  • Pedestrian re-identification method based on attribute feature and weighted block feature fusion
  • Pedestrian re-identification method based on attribute feature and weighted block feature fusion

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Embodiment Construction

[0037] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0038] A pedestrian re-identification method based on the fusion of attribute features and weighted block features, such as figure 1 shown, including the following steps:

[0039] Step 1. Construct an attribute feature extraction sub-network, which combines the manually extracted features and the features extracted by the deep neural network. The specific implementation method of this step is as follows:

[0040] The manual feature extraction method is: divide the pedestrian image into 16 horizontal blocks, and each block extracts 8-channel color features (including: RGB, HSV, YCbCr), and 21-channel texture features (including: 8 Gabor filters and 13 Schmid filters), after concatenating the features of each channel, the dimension is reduced to 1600 dimensions through the principal component analysis (PCA) method, and then mapped to 1024 dim...

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Abstract

The invention relates to a pedestrian re-identification method based on the fusion of attribute features and weighted block features, comprising the following steps: constructing an attribute featureextraction sub-network, which integrates the manually extracted features and the features extracted by a depth neural network; using A weighted cross-entropy loss function to train the attribute feature extraction subnetwork; constructing A block-based feature extraction sub-network, which can fuse the depth features of multiple blocks. Training the sub-network based on block feature extraction, setting the weighted fusion layer of local loss function, learning different weights independently, and then endowing each local loss function; training the whole network to extract the pedestrian feature representation which combines the attribute feature and the depth feature based on the block. The invention is reasonable in design, effectively combines attribute features and depth features, optimizes the loss function calculation method, obtains a good pedestrian recognition result, and greatly improves the overall matching accuracy of the system.

Description

technical field [0001] The invention belongs to the technical field of computer vision pedestrian re-identification, in particular to a pedestrian re-identification method based on the fusion of attribute features and weighted block features. Background technique [0002] At present, with the rapid development of video capture technology and large-scale data storage technology, it is possible to apply a large number of surveillance camera systems in public places. In the massive surveillance video data, the identification and processing of pedestrians is a major trend in technology development. Relying only on human eyes to identify pedestrian identities in surveillance images is obviously very inefficient. The task of pedestrian re-identification technology is to use computer vision technology to solve the problem of pedestrian identity matching in non-overlapping surveillance views, which is a major research hotspot at present. [0003] In recent years, with the rise of d...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/10G06F18/253Y02T10/40
Inventor 胡潇王琳王强付光涛姜竹青门爱东
Owner ACADEMY OF BROADCASTING SCI STATE ADMINISTATION OF PRESS PUBLICATION RADIO FILM & TELEVISION
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