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HOG를 이용한 손 형태 영상 인식Hand Gesture Recognition by Using Histograms of Oriented Gradients

Other Titles
Hand Gesture Recognition by Using Histograms of Oriented Gradients
Authors
신현철
Issue Date
Jun-2011
Publisher
대한전자공학회
Citation
대한전자공학회 하계학술대회, v.34권, no.1호, pp.761 - 764
Journal Title
대한전자공학회 하계학술대회
Volume
34권
Number
1호
Start Page
761
End Page
764
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/37375
Abstract
Histograms of Oriented Gradients (HOG) were successfully used for the detection of human beings. In this paper, we adopted the HOG to recognize hand gestures. First, we find the gradient vectors from input images and make a histogram for each cell. Then support vector machine is used to recognize hand gestures. Currently, a single hand gesture or two hand gestures in an image can be recognized. The hand gestures can be used to give commands to computes or other equipments. Experimental results show 98 ~ 99% recognition rate for normalized images and 94 ~ 98% recognition rate for non-normalized images, for three hand gestures. When two hand gestures are shown in an image 90% recognition rate is achieved.
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COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

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