Dynamic Gesture Recognition using SVM and its Application to an Interactive Storybook

SVM을 이용한 동적 동작인식: 체감형 동화에 적용

  • 이경미 (덕성여자대학교 컴퓨터학과)
  • Received : 2013.02.14
  • Accepted : 2013.03.26
  • Published : 2013.04.28


This paper proposes a dynamic gesture recognition algorithm using SVM(Support Vector Machine) which is suitable for multi-dimension classification. First of all, the proposed algorithm locates the beginning and end of the gestures on the video frames at the Kinect camera, spots meaningful gesture frames, and normalizes the number of frames. Then, for gesture recognition, the algorithm extracts gesture features using body parts' positions and relations among the parts based on the human model from the normalized frames. C-SVM for each dynamic gesture is trained using training data which consists of positive data and negative data. The final gesture is chosen with the largest value of C-SVM values. The proposed gesture recognition algorithm can be applied to the interactive storybook as gesture interface.


Supported by : 덕성여자대학교


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