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Gait recognition method based on deep learning

A gait recognition and deep learning technology, applied in the field of computer vision and pattern recognition, can solve the problem of low precision and achieve high accuracy

Active Publication Date: 2015-01-21
WATRIX TECH CORP LTD
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Problems solved by technology

[0004] In order to solve the problem that the existing gait recognition technology has low accuracy when dealing with cross-view gait recognition, the present invention proposes a gait recognition method based on deep learning, which uses a gait energy map to describe the gait sequence. A convolutional neural network trains a matching model to match gait recognition to a person's identity

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  • Gait recognition method based on deep learning

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0035] In order to better describe in conjunction with specific embodiments, this embodiment is described in conjunction with actual test examples, wherein the test process is equivalent to the recognition process in actual applications, and the test gait video is equivalent to the single-view gait to be identified in actual applications. live video.

[0036] In this embodiment, a dual-channel convolutional neural network with shared weights is used to construct a matching model based on a convolutional neural network. The model includes a feature extraction function module and a perceptron function module. This embodiment specifically includes a training process and a testing process, combined with figure 1 , figure 2 ...

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Abstract

The invention discloses a gait recognition method based on deep learning. The gait recognition method based on deep learning is characterized that identity of a person in a video is recognized according to gaits of the person through weight-shared two-channel convolutional neural networks by utilizing strong learning ability of the convolutional neural networks in a deep learning mode. The method has strong robustness on gait changes crossing large view angles, effectively solves the problem that accuracy is low when existing gait recognition technologies are used for recognizing gaits crossing view angles. The method can be widely applied to scenes with video monitoring, such as safety monitoring in airports and supermarkets, personnel recognition and criminal detection.

Description

Technical field [0001] The invention relates to computer vision and pattern recognition, and in particular to a gait recognition method based on deep learning. Background technique [0002] Among gait recognition methods, a common method is to first obtain a person's outline from all video sequences, calculate its gait energy image (GEI), and then compare the differences between different gait energy images. Similarity, and finally matching through a nearest neighbor classifier. However, previous methods are difficult to achieve practical accuracy when encountering serious cross-view problems. [0003] Deep learning theory has achieved very good results in the fields of speech recognition, image target classification and detection, etc. In particular, deep convolutional neural networks have very strong autonomous learning capabilities and a high degree of nonlinear mapping, which provides a good foundation for designing complex and high-precision systems. Classification mo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/66
CPCG06V30/194G06V2201/07
Inventor 谭铁牛王亮黄永祯吴子丰
Owner WATRIX TECH CORP LTD
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