Partitioned matrix-based gait recognition method

A block matrix and gait recognition technology, applied in the field of pattern recognition, can solve the problems of unsimplified feature extraction, low recognition accuracy, and huge data volume, and achieve the effect of improving recognition speed, recognition accuracy, and recognition accuracy

Inactive Publication Date: 2009-07-22
HARBIN ENG UNIV
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Problems solved by technology

However, when performing gait recognition, there is a substantial problem: the amount of data is too large
However, these methods have problems such as large amount of calculation and low recognition accuracy due to unsimplified feature extraction.

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  • Partitioned matrix-based gait recognition method
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  • Partitioned matrix-based gait recognition method

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Embodiment Construction

[0033] The present invention is described in more detail below in conjunction with accompanying drawing example:

[0034] 1. In order to extract the human target, first extract a single frame image from the original video for grayscale transformation (as shown in Figure 2(a)); then calculate the median value of each pixel in frame by frame as the background image of the entire sequence (as shown in Figure 2(b)); finally, the background subtraction method is used to extract the human body target (as shown in Figure 2(c)), and mathematical morphology is used to fill the holes in the binarized image, and simple connectivity analysis is used to extract the silhouette of the person (as shown in Figure 2 (d)). In order to eliminate the influence of image size on recognition, the human body should be centered, and the image size should be unified to 64*64 pixels (as shown in Figure 2(e)).

[0035] 2. Periodic detection of gait

[0036] image 3 To explain the positioning of the ell...

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Abstract

The invention provides a gait recognition method based on a partitioned matrix. Firstly, extracting single-frame images from a video, then carrying out grey scale transformation on the single-frame images, using the background subtraction method to extract person body targets, using mathematical morphology to fill the holes of binary images, and extracting profiles of the person by means of single connection analysis so that the person bodies are positioned in the middle and are uniformly in the size of 64 * 64 pixels; observing the periodic change of the gait according to elliptical short axis and eccentricity fitted in image regions after the standard centralization of each frame image in a gait video sequence; using a gait energy diagram to extract the integral characteristic of the gait in the one period, dividing GEI into sub-blocks by means of the partitioned matrix, eliminating the sub-blocks which are useless to classification in a self-adapting manner, and adopting the method, which combines the two-dimensional principal component analysis of a sub-block mode with the two-dimensional linear discriminant analysis, to further extract local characteristics; and integrating the characteristics of each effective sub-block into a whole during the classification recognition, and adopting a nearest neighbor classifier to perform identification judgment. The method is effective for the recognition of the gait of knapsack change.

Description

(1) Technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a gait recognition method. (2) Background technology [0002] With the demand for intelligent visual surveillance systems in security-sensitive places (banks, airports, etc.), some traditional biometric identification systems are difficult to meet the needs of practical applications. This kind of non-contact long-distance identification research—the second-generation biometric identification technology based on motion vision has attracted extensive attention of researchers. Biometrics such as faces and fingerprints usually require close-range or tactile sensing. They would be impossible to use at long distances, and gait is now the only biometric feature that is difficult to hide, difficult to camouflage, and captureable to perceive without being known to the person being observed. Therefore, gait recognition technology has important social and scien...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46
CPCG06K9/00348G06V40/25
Inventor 王科俊贲睍烨冯伟兴刘丽丽王晨晖崔建文
Owner HARBIN ENG UNIV
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