Abstract: Gesture recognition is the mathematical interpretation of a human motion by a computing device.It can originate from any bodily motion or state but commonly originate from the face or hand. It focuses in the field include emotion recognition from the face and hand gesture recognition. It presents a vision-based user interface designed to achieve computer accessibility for disabled users with motor impairments. Recognizing gestures as input allows computers to be more accessible for the physically-impaired and makes interaction more natural in a gaming or 3-D virtual world environment. Therefore, it is necessary to develop easily accessible systems for computers to achieve their inclusion within the new technologies. These applications involving hidden Markov models, particle filtering and condensation, are discussed in detail. Hidden Markov models (HMMs) and related models have become standard in statistics, with applications in areas like speech and other signal processing, bioinformatics etc. Markov chain Monte Carlo (MCMC) is great stuff. MCMC revitalized Bayesian inference and frequents inference about complex dependence.


Keyword: gesture recognition, particle filtering, HCI