Static gesture characteristic describing method based on tetragon skeleton structure

A skeleton structure and feature description technology, applied in the field of static gesture feature description based on quadrilateral skeleton structure, can solve the problems of long time, low accuracy of complex gesture recognition, and inability to meet the requirements of real-time extraction of feature gestures.

Inactive Publication Date: 2009-02-04
XIAN UNIV OF TECH
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Problems solved by technology

[0003] The feature description of static gestures is a key link in gesture recognition technology. The existing feature descriptions of static gestures mostly use methods such as invariant moments, Fourier descript...

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  • Static gesture characteristic describing method based on tetragon skeleton structure
  • Static gesture characteristic describing method based on tetragon skeleton structure
  • Static gesture characteristic describing method based on tetragon skeleton structure

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Embodiment Construction

[0046] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] The method of the present invention first utilizes the existing skin color detection method to extract the binary gesture template generated by the gesture area, then constructs a quadrilateral skeleton structure according to the binary gesture template, and generates static gesture features according to the constructed quadrilateral skeleton structure, the method is as follows Steps to proceed:

[0048] Step 1: Extract the gesture area in the captured static gesture video frame

[0049] Using the existing skin color detection method, the specific static gesture displayed by the human hand is shot in the RGB color system, and the gesture area in the obtained video frame is converted to the YIQ color system according to the following formula, and it is extracted to generate Such as figure 1 The binary template for this gesture area is...

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Abstract

The invention discloses a static hand gesture description method based on the quadrangle skeleton structure; the skin-color region is detected to obtain the binary mask of the static hand gesture region; then the contour-rectangle is constructed according to the binary mask and is equally divided into four sub rectangles; the centroids of the binary mask pixel point sets in the four sub rectangles are searched in the four sub rectangles; the four centroids are connected to construct a quadrangle skeleton used for indicating different hand gestures; then six perimeter ratios, four angle perimeter ratios and four rectangle degrees of the quadrangle skeleton are extracted and used as the description characteristic values; the description characteristic values are processed normalization to form the 14-dimensional characteristic vector for expressing different static hand gestures. The static hand gesture description method not only can recognize the characteristics of the common hand gestures, but also can recognize the characteristics of the complex static hand gestures, so as to satisfy the real-time processing requirement and improve the recognition correct rate of the complex hand gestures.

Description

technical field [0001] The invention belongs to the technical field of image biological feature recognition, and relates to a static gesture feature description method, in particular to a static gesture feature description method based on a quadrilateral skeleton structure. Background technique [0002] Gesture recognition, a related technology belonging to the category of body language recognition, is a biometric recognition technology; it can be used in human-computer interaction, dumb language translation and other fields. Gestures can be defined as static gestures and dynamic gestures according to their motion states. [0003] The feature description of static gestures is a key link in gesture recognition technology. The existing feature descriptions of static gestures mostly use methods such as invariant moments, Fourier descriptors, and intersection statistics, but these methods are correct for the recognition of complex gestures. The rate is low and time-consuming, w...

Claims

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Application Information

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IPC IPC(8): G06K9/00
Inventor 朱虹金欢徐骁斐赵朝杰孙国清曹建斌许洁韩永鹏吴瑞杰王栋
Owner XIAN UNIV OF TECH
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