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A Dynamic Gesture and Posture Recognition System
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DOI：10.1007/s10846-013-9983-7.png)
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This paper presents a real time dynamic hand gesture and posture recognition system based on a neural network and a Hidden Markov Model. For skin color segmentation an adaptive online trained skin color model is used, while the hand posture recognition is accomplished through a likelihood-based classification technique of geometric features. A novel trajectory smoothing technique based on Self Organized Neural Network is introduced to improve HMM classification performance of dynamic gestures. The aim of the proposed system is the creation of a visual dictionary combining hand postures and dynamic gestures. The system has been successfully tested with many people under varying light conditions and different web cameras.
Keyword:
Human computer interaction
Hand posture
Dynamic gesture
Skin color detection
Artificial neural network
Hidden Markov Model
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被引数:
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PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
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