In this paper we address the object recognition problem in a probabilistic framework to detect and describe object appearance through image features organized by means of active c...
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
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. ...
In this paper, we introduce a first-order probabilistic model that combines multiple cues to classify human activities from video data accurately and robustly. Our system works in...
An approach to recognise and segment 9 elementary gestures from a video input is proposed and it can be applied to continuous sign recognition. An isolated gesture is recognised b...