Static gesture identification method based on vision

A gesture recognition and gesture technology, applied in character and pattern recognition, instruments, computing, etc., can solve problems such as non-smoothness, difficulty in gesture target recognition, and easy shadowing, and achieve good recognition rate, good recognition effect, and high recognition rate. Effect

Inactive Publication Date: 2010-03-03
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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Problems solved by technology

[0008] (2) Difficulties in gesture target recognition
[0012] c) The position is in three-dimensional space, so it is difficult to locate, and the image acquired by the compute

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  • Static gesture identification method based on vision
  • Static gesture identification method based on vision
  • Static gesture identification method based on vision

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Embodiment Construction

[0023] Such as figure 1 As shown, the present invention provides a static gesture recognition method based on vision, which includes the following steps: S1 gesture image preprocessing, segmenting the hand area from the environment according to the skin color characteristics of the human body, and then obtaining the gesture through image filtering and image morphology operations Contour; S2 gesture feature parameter extraction, extracting Hu invariant moment feature, gesture region feature and Fourier descriptor parameters to form a feature vector; S3 gesture recognition part, using a multi-layer perceptron classifier, which has self-organization and self-organization Learning ability, can effectively resist noise and deal with incomplete patterns, and has the ability to generalize patterns.

[0024] The step S1 includes S11 binarizing the gesture image, S12 smoothing filter denoising and S13 contour extraction.

[0025] S11 Binarized gesture image: Binarize the original gest...

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Abstract

The invention provides a static gesture identification method based on vision, comprising the following steps of S1, gesture image pretreatment: separating a hand region from an environment accordingto the complexional characteristic of a human body and obtaining a gesture profile through image filtering and image morphological operation; S2, gesture characteristic parameter extraction: extracting an Hu invariable moment characteristic, a gesture region characteristic and a Fourier description subparameter so as to form a characteristic vector; and S3, gesture identification, using a multi-layer sensor classifier having self-organizing and self-studying abilities, capable of effectively resisting noise and treating incomplete mode, and having mode generalization ability. The static gesture identification method based on vision in the invention firstly carries out pretreatment and binarizes the original gesture image according to the complexional characteristic of the human body. The extracted gesture characteristic parameters are in three groups, namely the Hu invariable moment characteristic, the gesture region characteristic and the Fourier description subparameter, which form the characteristic vector together. The characteristic has better recognition rate.

Description

technical field [0001] The present invention relates to a control method, especially one that is applied to many aspects such as computer-aided dumb language teaching, bilingual broadcasting of TV programs, virtual human research, special effects processing in film production, animation production, medical research, game entertainment, etc. It is also helpful to improve and improve the living, learning and working conditions of the deaf-mute, and provide them with a vision-based static gesture recognition method for better services. Background technique [0002] In 1991, Fujitsu Laboratories completed the recognition of 46 sign language symbols [0003] In December 2003, the Cybernet System Company in Michigan, USA developed a system called Gesture Storm, which was developed by the company for the weather forecast program. The host can control the forecast process through simple gestures. [0004] In 2008, scientists at a research laboratory of Japan's Toshiba Corporation a...

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Application Information

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IPC IPC(8): G06K9/00
Inventor 王轩吴堃于成龙王茂吉
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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