This paper presents an unsupervised segmentation method for feature sequences based on competitivelearning hidden Markov models. Models associated with the nodes of the Self-Organ...
The scope of this paper is the interpretation of a user's intention via a video camera and a speech recognizer. In comparison to previous work which only takes into account g...
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
We present a novel technique for the recognition of complex human gestures for video annotation using accelerometers and the hidden Markov model. Our extension to the standard hid...
Graeme S. Chambers, Svetha Venkatesh, Geoff A. W. ...
We consider the problem of computing the likelihood of a gesture from regular, unaided video sequences, without relying on perfect segmentation of the scene. Instead of requiring ...