Hand Posture Recognition for Complex Decision Making
Gesture recognition can be seen as a way for
computers to begin to understand human body language, thus building a richer bridge between machine and humans than primitive text, user interfaces or even GUI’s. Gesture recognition method used in this paper aims on recognizing hand postures as well as facial expressions. Here, facial expressions are used as context for the gesture recognized that helps in giving additional information about
the gestures performed. Thus the information obtained from this static posture defines a particular gesture.
We also have described another method which uses previous
frame as its context and recognize the gesture performed. Many a times, a gesture recognized can have multiple meaning, or its actual
meaning cannot be easily recognized by just extracting features from one frame. So, in such situations we can use previous frame of the
gesture performed and extract its features. The information obtained from these features can then be used to avoid the ambiguity in meaning and the gesture can be recognized accurately. These gestures
then can be used to make some complex decisions, ultimately driving an application.
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