Gait segmentation and gait recognition integrated method based on deep learning

A gait recognition and deep learning technology, applied in character and pattern recognition, instruments, biological neural network models, etc., to achieve the effect of accelerating speed

Active Publication Date: 2016-07-13
WATRIX TECH CORP LTD
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Problems solved by technology

[0003] The purpose of the present invention is to solve the problems encountered in gait recognition in real scenes in the prior art, and propose a gait segme

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  • Gait segmentation and gait recognition integrated method based on deep learning
  • Gait segmentation and gait recognition integrated method based on deep learning

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Embodiment Construction

[0019] In the following, the technical solution of the present invention will be further described in detail through the drawings and embodiments.

[0020] The gait segmentation and gait recognition integration method based on deep learning provided by the present invention uses deep learning technology to jointly train the N-channel segmentation convolutional neural network model (gait segmentation model) and classification convolutional neural network model (gait recognition model), first train a multi-channel gait segmentation model, then train a gait recognition model, and finally perform joint training, which achieves very high accuracy and speed on gait recognition tasks in real scenes.

[0021] Next, take a large gait recognition database as an example. The large gait recognition database contains gait video sequences of 138 people, each with about 36 videos, including different viewing angles, backgrounds and clothing, used for gait segmentation model initialization Th...

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Abstract

The invention discloses a gait segmentation and gait recognition integrated method based on deep learning. According to the method, human figure contour segmentation is performed on multiple gait images in a segment of gait video by utilizing a multichannel neural network segmentation model so that human figure contour segments of multiple gait images in the segment of gait video are acquired; and then identity recognition is performed on the acquired human figure contours through a classification convolution neural network model, and an identity recognition result is outputted. The method has extremely high robustness on scene changes, dressing changes, the angles of the image video and the walking state, and the method is especially suitable for solving gait recognition under the dynamic background and can achieve extremely high recognition precision in the actual gait recognition; and an integrated framework of segmentation and recognition is adopted so that the method also has extremely high recognition speed and is suitable for real-time gait recognition under the actual monitoring.

Description

technical field [0001] The invention relates to the technical fields of computer vision, pattern recognition and gait recognition, in particular to an integrated method of gait segmentation and gait recognition based on deep learning. Background technique [0002] In the gait recognition method, most of the methods need to be divided into three steps: gait image segmentation, feature extraction and gait recognition. The feature extraction is mainly based on the gait energy image (GaitEnergyImage, GEI) and then the feature change. The computational complexity is high, the speed is relatively slow, and it depends on accurate segmentation results. If the gait image segmentation results are poor, subsequent recognition cannot be achieved. Therefore, most traditional algorithms require the background to be static or simple, and the ideal human figure segmentation results cannot be obtained under the complex and dynamic background conditions in the real monitoring environment. T...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/02
CPCG06N3/02G06V40/25G06F18/24
Inventor 黄永祯谭铁牛王亮宋纯锋
Owner WATRIX TECH CORP LTD
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