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Pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion

A multi-feature fusion and attribute recognition technology, applied in the field of computer vision, can solve problems such as inaccurate label recognition and pixel analysis area deviation, and achieve the effect of improving image quality, accurate recognition, and simple methods

Active Publication Date: 2022-08-09
FUZHOU UNIV
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a pedestrian clothing attribute recognition method based on depth attitude estimation and multi-feature fusion, to overcome the defects in the prior art, and to solve the problems of inaccurate label recognition and pixel analysis area deviation under a single analysis method question

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  • Pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion
  • Pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion
  • Pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion

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Embodiment Construction

[0078] The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

[0079] like figure 1 As shown, the present invention provides a pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion. Aiming at the problem that the existing attribute recognition methods have the interference of environmental factors and thus affect the positioning accuracy, a pedestrian attribute recognition method based on pedestrian pose estimation and multi-feature fusion is proposed. The method firstly matches appearance features and selects some retrieval results for subsequent attribute identification. Then, through the deep human pose estimation method based on SSD, the foreground area belonging to pedestrians in the image can be effectively located, and the interference of background factors can be better excluded. Finally, the analysis results of various methods are combined, co...

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Abstract

The invention relates to a pedestrian clothing attribute recognition method based on depth pose estimation and multi-feature fusion. The method first selects some retrieval results for subsequent attribute recognition through appearance feature matching; then through the SSD-based deep human pose estimation method, it can effectively locate the foreground area belonging to pedestrians in the image, and better eliminate the interference of background factors Finally, the analysis results of various methods are combined, combined with the iterative smoothing process, the maximum a posteriori probability distribution method is adopted to strengthen the correlation between attribute labels and pixels, and the final attribute analysis and recognition results are obtained. The invention solves the problems of inaccurate label identification and pixel analysis area deviation under a single analysis mode. The method is simple and flexible, and has strong practical applicability.

Description

technical field [0001] The invention belongs to the fields of computer vision, deep learning, and image processing, and is applied to scenarios such as intelligent monitoring and pedestrian re-identification, in particular to a pedestrian clothing attribute recognition method based on depth posture estimation and multi-feature fusion. Background technique [0002] Pedestrian attribute recognition in surveillance images obtained from surveillance video is challenging in the real world for the following reasons: (1) the imaging quality is poor, the resolution is usually low, and it is easily affected by motion blur; (2) the attributes may Because of the influence of the appearance of the clothes worn or worn by pedestrians, and because of the different postures of pedestrians in different images, the corresponding attributes are located in different spatial positions in the image; (3) It is difficult to collect labeled attribute data from surveillance video images. And only av...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/774G06V10/762G06V10/764G06V10/46G06V10/82G06K9/62G06N3/04G06T5/00
CPCG06T5/002G06V10/464G06N3/045G06F18/23213G06F18/214G06F18/24143
Inventor 柯逍李振达
Owner FUZHOU UNIV
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