Pedestrian reidentification method and system based on color texture distribution characteristic

Abstract

The invention belongs to the image processing technology field and relates to a pedestrian reidentification method based on a color texture distribution characteristic. The method comprises the following steps of inputting N image pairs to be matched including training data and test data and a corresponding label ln, wherein the n=1,..., N; extracting the color texture space distribution characteristic expression of input image data; acquiring the consistent characteristic expression of the color texture space distribution characteristic expression through multi-scale characteristic matching;and constructing two classifiers for the acquired consistent characteristic expression and outputting a probability expression describing a same target. The method has advantages that characteristic extraction is simple and a speed is fast; a training period is short; robustness is high; and precision is high.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a pedestrian re-identification method based on color texture distribution features, in particular to a deep learning method for pedestrian re-identification by a feature construction method representing image color texture distribution information. Background technique [0002] The task of pedestrian re-identification is to deal with the problem of cross-camera pedestrian matching. The application of this technology in the pedestrian monitoring network is reflected in pedestrian tracking, human body retrieval, etc. The pedestrian tracking application is to use the existing urban monitoring network to retrieve the pedestrian target to be tracked in each camera. By connecting the camera where the target appears, the movement track of the target pedestrian can be obtained, so as to complete the tracking of the target pedestrian. Human body retrieval is to retrieve the target ...

AI Technical Summary

Problems solved by technology

However, how to effectively express this information is one of the bottlenecks affecting the development of pedestrian re-identification technology.

At present, some methods at home and abroad are often based on the assumption that the pedestrians in the image remain upright, slice the pedestrian image in the vertical direction, and obtain some significant color and texture distribution features for each slice, but because of the change of the camera angle of view, the two The corresponding slices of pedestrian images do not necessarily describe the common parts of pedestrians, resulting in poor performance in complex scenes

[0004] At present, there are certain limitations and deficiencies in the construction and extraction of image texture features in the task of pedestrian re-identification: 1. Loss of spatial distribution information of color texture features

For a long time, the processing of color and texture features in the field of computer vision is often a histogram of color or texture distribution in a statistical area, and expressed in the form of a one-dimensional vector. One of the main problems caused by this method is the loss of spatial information.

2. Lack of high-level feature description methods for describing image color texture

For a long time, image-based color and texture features are often obtained directly from the original image. Due to the impact of the input image scale, the traditional feature description method lacks an effective abstraction and encoding mechanism for color and texture features, so it cannot overcome the contradiction between the curse of dimensionality and information loss.

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