Gesture Recognition and HMM

Understanding human motions can be posed as a pattern recognition problem. Humans express time-varying motion patterns (gestures), such as a wave, in order to convey a message to a recipient. If a computer can detect and distinguish these human motion patterns, the desired message can be reconstructed, and the computer can respond appropriately. This thesis describes an approach to recognize domain-dependent gestures using various different mehods. Constellation method and Hidden Markov Model (HMM) are one of the different methods of gesture recognition. Both methods have their special features and used according to appropriate situations. HMM involves more mathematical calculations than constellation method.

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