Gait recognition method and system, equipment and storage medium

A gait recognition and gait technology, applied in the field of computer vision, can solve the problems of low accuracy and achieve good real-time performance, good gait recognition effect, and good recognition effect

Pending Publication Date: 2021-10-08
GUANGDONG POLYTECHNIC NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented describes an improved way for identifying walking patterns that can help improve athletic performance or reduce muscle fatigue during physical exercise. It uses advanced techniques such as convolutional neural networks (CNNs) to extract specific areas from image data representing these movements. These technical improvements make it easier than previous methods without sacrificing accuracy due to factors like depth perception limitations. Overall this innovation improves how well people learn their movement over longer periods of training while still being able to recognize different types of footwear with greater detail at varying angles.

Problems solved by technology

This technical problem addressed in this patents relates to improving the performance of ghost detection systems used during motion analysis (MCA) on images captured through cameras mounted inside buildings that change their orientation frequently over time. Current techniques have limitations when applied across multiple perspectives: they cannot accurately recognize objects moving around within an indoor environment like walls or doors, which may be important applications where accurate tracking is crucial. Additionally, current approaches focus heavily on identifying specific parts of the person's body based solely upon image content alone, leading to poor recognition rates despite significant variations between individuals.

Method used

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  • Gait recognition method and system, equipment and storage medium
  • Gait recognition method and system, equipment and storage medium
  • Gait recognition method and system, equipment and storage medium

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Embodiment Construction

[0052] The embodiment of the present invention will be explained in detail below in conjunction with the accompanying drawings. The examples given are only for the purpose of illustration, and cannot be interpreted as limiting the present invention. The accompanying drawings are only for reference and description, and do not constitute the scope of patent protection of the present invention. limitations, since many changes may be made in the invention without departing from the spirit and scope of the invention.

[0053]Aiming at the problem that the existing gait recognition method not only divides the features of each part of the human body, but also extracts the features of each frame of gait video with equal probability, resulting in low recognition accuracy under cross-angle and complex conditions, this paper The embodiment of the invention provides a gait recognition method, system, device and storage medium, see figure 1 , figure 1 It is a schematic flow chart of a gait r

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Abstract

The invention relates to the technical field of computer vision, in particular to a gait recognition method and system based on space-time slice features, equipment and a storage medium, and the method comprises the steps: associating features from adjacent body parts from top to bottom through a slice extraction device, and learning the weight of each frame through a residual frame attention mechanism, and weighting each frame of the gait contour sequence, so that the network can pay more attention to the frames with high contributions. According to the method and system, a residual frame attention mechanism and slice features are combined in parallel, and key frame screening can be flexibly carried out on each adjacent feature of a human body, so that the method provided by the invention has relatively high gait recognition accuracy under cross view angles and complex conditions; in addition, any number of video frames can be input, and the method and system have the advantages of being simple and flexible in model, wide in application range and good in real-time performance.

Description

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Claims

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Application Information

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Owner GUANGDONG POLYTECHNIC NORMAL UNIV
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