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A pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning

A pedestrian re-recognition and dictionary learning technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as difficulty in matching similar pedestrians, and achieve good results

Active Publication Date: 2019-03-08
KUNMING UNIV OF SCI & TECH
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  • Application Information

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Problems solved by technology

[0005] The present invention provides a pedestrian re-identification method based on label consistency constraints and stretching regularized dictionary learning, which is used to solve the problems caused by the great similarity, illumination and posture changes of different pedestrians in the prior art. Pedestrian matching problem

Method used

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  • A pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning
  • A pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning
  • A pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning

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Embodiment 1

[0040] Embodiment 1: as figure 1 As shown, a pedestrian re-identification method based on label consistency constraints and stretched regularized dictionary learning, the specific steps of the pedestrian re-identification method based on label consistency constraints and stretched regularized dictionary learning are as follows:

[0041] Step1. Construct training samples and test samples of feature data from two perspectives;

[0042] The concrete steps of described step Step1 are as follows:

[0043] Step1.1. Extract LOMO features from the pictures on the public dataset;

[0044] Step1.2, and then reduce the dimensionality of the feature data, the data of each picture after dimensionality reduction is a column vector (n×1), as a sample of a pedestrian under one viewing angle; the sample data of all pedestrians under one viewing angle is the feature matrix (n×m), n is the dimension of the feature, and m is the number of pedestrians;

[0045] Step1.3. Obtain the feature matri...

Embodiment 2

[0068] Embodiment 2: as figure 1 As shown, a pedestrian re-identification method based on label consistency constraints and stretched regularized dictionary learning, the specific steps of the pedestrian re-identification method based on label consistency constraints and stretched regularized dictionary learning are as follows:

[0069] Step1. Construct training samples and test samples of feature data from two perspectives;

[0070] The concrete steps of described step Step1 are as follows:

[0071] Step1.1. Randomly select 316 pedestrians from the pictures on the public VIPeR dataset to be divided into a training set, and the remaining 316 pedestrians are used as a test set for LOMO feature extraction; figure 2 Pedestrian images under two perspectives randomly extracted from the public dataset VIPeR commonly used for pedestrian re-identification in the present invention, the upper column is the pedestrian image of the a perspective, and the next column is the pedestrian im...

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Abstract

The invention relates to a pedestrian recognition method based on label consistency constraint and stretch regularization dictionary learning, belonging to the technical field of digital image recognition. At first, that original image features are mapped to a low-dimensional discrimination space to reduce the divergence between the same pedestrian unde different angles of view. In addition, in order to further enhance the discriminability of the dictionary, it is assumed that the same pedestrian enjoys the same coding coefficient in the low-dimensional space, and the stretching regularity term is added to force the pedestrians with similar visual features but different identities to have large coding coefficients. In order to fully mine label information of label samples, label consistency constraints are added, and a dictionary learning model based on the combination of dictionary and classifier is constructed. In the test phase, pedestrian recognition is carried out by similarity measurement based on the parameters learned from the dictionary learning model. The method provided by the invention has the higher recognition rate than the traditional method.

Description

technical field [0001] The invention relates to a pedestrian re-identification method based on label consistency constraints and stretching regularized dictionary learning, belonging to the technical field of digital image recognition. Background technique [0002] Pedestrian re-identification, also known as pedestrian re-identification or re-verification, is a technology to determine whether the pedestrians captured by non-overlapping cameras are the same pedestrian. Because this technology is one of the important tasks in intelligent monitoring, it has a strong use value. In reality, the resolution of the collected video images of pedestrians is often low, and in many cases the multiple biological characteristics of pedestrians are not obvious, so traditional biometric-based methods cannot be used to identify them. At the same time, due to the change of viewing angle and illumination and the difference in camera imaging style, the same pedestrian shows different visual ch...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/213G06F18/22
Inventor 李华锋周维燕许佳佳
Owner KUNMING UNIV OF SCI & TECH
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