Multi-rotating direction SVM model gesture tracking method based on HOG characteristics

A technology of rotation direction and model, applied in the field of image processing and pattern recognition, to achieve the effect of improving accuracy, satisfying real-time, and ensuring quality

Active Publication Date: 2015-06-24
BEIHANG UNIV
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Problems solved by technology

[0005] The purpose of the invention is to solve the problem of rotation of specified gestures in the plane, and improve the positioning of specified gestures using the multi-rotation direction SVM model based on HOG features

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  • Multi-rotating direction SVM model gesture tracking method based on HOG characteristics
  • Multi-rotating direction SVM model gesture tracking method based on HOG characteristics
  • Multi-rotating direction SVM model gesture tracking method based on HOG characteristics

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Embodiment Construction

[0030] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

[0031] The present invention studies a gesture tracking method based on the HOG feature multi-rotation direction SVM model. This method uses the web camera to continuously capture the image frame in front of the mirror, and then judges through the tracking and positioning framework based on HOG+Multi-SVM Whether the specified gesture is included in the frame, find out the index number of its direction subsection, and locate its position in the frame. The invention effectively improves the positioning of prescribed gestures by using the multi-rotation direction SVM model based on HOG features. Multi-SVM refers to multivariate support vector machine (Multi.SupportVectorMachine, Multi-SVM), and the present invention refers to the SVM model of multiple direction subintervals in plane space.

[0032] Generally speaking, the method proposed in the present ...

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Abstract

The invention discloses a multi-rotating direction SVM model gesture tracking method based on HOG characteristics. Images continuously grabbed by a Web camera serve as input images, and the set gesture initial detecting positioning and later tracking positioning are carried out on the frames of the images. A HOG+Multi-SVM detecting module is used for obtaining the set gesture detected and positioned in front several frames of gesture images from the Web camera; under the situation that the image frames include the set gesture, a gesture tracking module of a multi-rotating direction SVM model based on the HOG characteristics is started for tracking positioning; once the tracking module loses the tracking for the set gesture or the gesture is moved out of the shooting range of the Web camera, the HOG+Multi-SVM detecting module is started again till the set gesture can be continuously detected and positioned successfully. The speed for positioning the set gesture can be effectively increased, and meanwhile the positioning precision for the set gesture is also improved.

Description

technical field [0001] The invention relates to a gesture tracking method of a multi-rotation direction SVM model based on HOG features, and belongs to the technical fields of image processing and pattern recognition. Background technique [0002] Nowadays, the popularization and rapid development of computers make people's life more and more dependent on computers, and computers are everywhere. In the previous human-computer interaction technology, specific input and output devices, such as keyboards, mice, stylus pens, scanners, etc., were widely used. In recent years, with the substantial improvement of computer performance, personal computers (PCs) have the capabilities of various communication media such as voice processing and graphic image processing. In order to improve the ease of use of computers and the naturalness of human-computer interaction, new input technology has become a research hotspot that has attracted the attention of users and researchers. The rapi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F3/01G06K9/00
Inventor 牛建伟赵晓轲苏一鸣
Owner BEIHANG UNIV
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