ABSTRACT:
Understanding human
motions can be posed as a pattern
recognition problem. Humans express timevarying
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.
motions can be posed as a pattern
recognition problem. Humans express timevarying
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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