Gesture identification method and gesture identification system

A gesture recognition and gesture technology, applied in the field of gesture recognition, can solve problems such as the inability to meet real-time performance and the inability to use recognition algorithms

Inactive Publication Date: 2015-06-03
WINGTECH COMM
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0004] In addition, due to the limitations of the hardware conditions of the current mobile platform, an overly complex recognition algorithm cannot be used, otherwise it will not be able to meet the real-time requirements

Method used

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  • Gesture identification method and gesture identification system
  • Gesture identification method and gesture identification system

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Embodiment 1

[0156] The present invention proposes a gesture detection method based on LBP features. On the premise of detecting gestures, the detected region of interest is processed to segment gesture contours. Gesture segmentation is divided into three steps: skin color segmentation, edge detection and contour extraction. Then recognize the extracted gesture outline. Due to the limitation of the current mobile platform hardware conditions, an overly complicated recognition algorithm cannot be used, otherwise it will not be able to meet the real-time requirements. Gesture matching algorithm is still the biggest problem in the current gesture recognition process. The invention adopts a recognition algorithm based on principal component analysis and K-mean value clustering, uses principal component analysis to reduce the dimension of feature data, and then uses K-mean value clustering algorithm to classify.

[0157] The gesture recognition method of the present invention specifically comp...

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Abstract

The invention discloses a gesture identification method and a gesture identification system, wherein the method comprises the following steps: step S1, a gesture detecting step: detecting a gesture in video stream in real time, marking a region in which the gesture is detected as an interested region; step S2, a gesture segmenting step: processing the interested region by utilizing skin color segmentation, and then performing edge detecting and outline extracting to obtain a point sequence of a hand-shaped outline; step S3, a gesture identifying step: firstly extracting a Fourier descriptor of the hand-shaped outline and then mapping the Fourier descriptor to a new vector of a characteristic space by utilizing PCA (principal components analysis), comparing the distance between the new vector and a gesture clustering center obtained by training, and judging a gesture type represented by the vector. The gesture identification method and the gesture identification system disclosed by the invention can improve the gesture identification accuracy and the gesture identification efficiency, and can effectively avoid background color interference.

Description

technical field [0001] The invention belongs to the technical field of gesture recognition, and relates to a gesture recognition method, in particular to a gesture recognition method based on principal component analysis and K-means clustering; at the same time, the invention also relates to a gesture recognition method based on principal component analysis and K-means clustering gesture recognition system. Background technique [0002] Gesture, as a natural and intuitive means of human-computer interaction, has been a research hotspot in human-computer interaction technology for more than two decades, and computer-based gesture recognition technology is almost mature. In the past two years, the number of smart mobile terminal devices, especially Android devices, has grown rapidly. Many people are also studying other interactive methods besides touch, such as voice recognition technology. development trend. Recently, some applications that use body language interaction hav...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
Inventor 李保印
Owner WINGTECH COMM
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