Title :
Clustering Method Evaluation for Hidden Markov Model Based Real-Time Gesture Recognition
Author :
Prasad, Jay Shankar ; Nandi, G.C.
Author_Institution :
Robot. & AI Lab., Indian Inst. of Inf. Technol., Allahabad, India
Abstract :
This paper deals with the development of high performance real-time system for complex dynamic gesture recognition. The various motion features are extracted from the video frames which are used by HMM classifier. We used several clustering techniques for performance evaluation of the classifier. Our system vectorises gestures into sequential symbols both for training and testing. We found very encouraging results and the proposed method has potential application in the field of human machine interaction.
Keywords :
feature extraction; gesture recognition; hidden Markov models; human computer interaction; pattern classification; pattern clustering; real-time systems; video signal processing; classifier; clustering method; hidden Markov model; human machine interaction; motion feature extraction; real-time gesture recognition; video frames; Clustering methods; Data mining; Feature extraction; Hidden Markov models; Humans; Image recognition; Neural networks; Optical sensors; Principal component analysis; Real time systems; Clustering; Gesture; HMM;
Conference_Titel :
Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
Conference_Location :
Kottayam, Kerala
Print_ISBN :
978-1-4244-5104-3
Electronic_ISBN :
978-0-7695-3845-7
DOI :
10.1109/ARTCom.2009.99
