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The Research Of Real-time Hand Gesture Recognition System Based On Monocular Vision

Posted on:2016-03-14Degree:MasterType:Thesis
Country:ChinaCandidate:D X ZhengFull Text:PDF
GTID:2308330473459694Subject:Optical Engineering
Abstract/Summary:PDF Full Text Request
With the development of science and technology and the accumulation of social material wealth, people are pursueing higher living standard. currently,computer technology is linked closely to everyday life, applying a profund impact on our life, so HMI(Human-Machine-Interaction) manner is increasingly becoming a hotspot. Human-computer interaction is transforming from the machine-centered to user-centric. However, gesture recognition system based on monocular vision coincides this trend, it more fit the way human communicates. Hand gesture recognition system make HCI more friendly, naturely and conveniently, while hand is a tool for anyone born, it make HCI a unfied way to communicate with all the computers. but hand own high flexibility and complex structure, so hand gesture recognition system based on monocular vision is a very challenging research topic.This paper designed and implemented a hand gesture recognition system based on monocular webcam, it can recognized eight defined hand gesture. in addition, the paper also uses gesture recognition result achieved simulation of mouse function and a control of LED-Lamps group. The hand gesture recognition system divided to four modules: hand gesture preprocessing, gesture segmentation, feature extraction and classification.in the preprocessing module, wo modified the global light compensation algorithm to improve the quality of hand gesture image. in hand gesture segmentation module, the paper combined skin-feature and motion information to achive a robust hand gesture segmentation, and successfully implemented the adaptive skin model update, eliminating the inference of background object. In addition, it uses covex defect depth information and minimum bounding rectangle size of successful implementation of a crude gesture image classification, and uses the fourier desceiptors and SVM claasifier to classify the inseparable hand gesture, it achieved 97.5% recognition rate. The application of mouse and led lamp demonstrates that hand gesture have a very large potential in the field of multimedia and smart home field, and it have some practical value.
Keywords/Search Tags:HCI, Hand gesture recognition, Hand gesture segmentation, Background subtraction
PDF Full Text Request
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