(A) study on the gesture spotting from continuous hand motion with a threshold model = 임계치 모델을 이용한 연속적인 손 동작으로부터의 제스처 추출에 관한 연구

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This paper proposes a new method of spotting meaningful gestures from continuous hand motion in real-time. As the gesturer switches from one gesture to another, his hand makes an intermediate move linking the two gestures. A gesture recognizer may attempt to recognize this inevitable intermediate motion as a meaningful one (segmentation problem). Furthermore, the same gesture varies dynamically in shape and duration; instance by instance even of the same gesturer (spatio-temporal variability problem). The proposed method can solve the problems of segmentation and spatio-temporal variability of gestures using Hidden Markov Model (HMM). To handle non-gesture patterns between gestures, we make use of the internal segmentation property of the HMM and introduce a threshold model that consists of the state copies of all trained gesture models. The internal segmentation property implies that the states and the transitions of a trained HMM represent sub-patterns of a gesture and their sequential order. The threshold model calculates the likelihood threshold of the input pattern and is used to qualify an input pattern as a gesture. However, the threshold model, a weak model of all gestures, has a large number of states, so we reduce the number of states by the use of relative entropy. Through a set of experiments, it has been shown that the proposed method can successfully extract meaningful gestures from continuous hand motion with 93.14% reliability. The proposed method has been incorporated into PowerGesture to provide gestural commands for browsing the slide of $PowerPoint^TM$.
Advisors
Kim, Jin-Hyungresearcher김진형researcher
Description
한국과학기술원 : 전산학과,
Publisher
한국과학기술원
Issue Date
1998
Identifier
143507/325007 / 000955311
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 전산학과, 1998.2, [ viii, 86 p. ]

Keywords

State reduction; Relative entropy; Pattern recognition; Segmentation; Hidden Markov model; Gesture spotting; Hand gesture; Threshold model; 임계치 모델; 상태 줄이기; 상대성 엔트로피; 패턴인식; 구분; 은닉 마르코프 모델; 손 제스처; 제스처 적출

URI
http://hdl.handle.net/10203/33120
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=143507&flag=dissertation
Appears in Collection
CS-Theses_Ph.D.(박사논문)
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