We propose a modified Hidden Markov Model (HMM) with a view to improving gesture recognition in the moving camera condition. We define a new gesture recognition framework in which multiple candidates of feature vectors are generated with confidence measures and the HMM is extended to deal with these multiple feature vectors. Experimental analysis comparing the proposed system with feature vectors based on DCT and the method of selecting only one candidate feature point verify the effectiveness of the technique.
|Number of pages||5|
|Journal||Proceedings - International Conference on Pattern Recognition|
|Publication status||Published - 2002 Jan 1|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition