Real-time gesture recognition using deterministic boosting

A gesture recognition system which can reliably recognize single-hand gestures in real time on a 600Mhz notebook computer is described. The system has a vocabulary of 46 gestures including the American sign language letterspelling alphabet and digits. It includes mouse movements such as drag and drop, and is demonstrated controlling a windowed operating system, editing a document and performing file-system operations with extremely low error rates over long time periods. Real-time performance is provided by a novel combination of exemplar-based classification and a new "deterministic boosting" algorithm which can allow for fast online retraining. Importantly, each frame of video is processed independently: no temporal Markov model is used to constrain gesture identity, and the search region is the entire image. This places stringent requirements on the accuracy and speed of recognition, which are met by our proposed architecture.

• Type: Conference
• Year: 2002
• Where: BMVC
• Authors: Raymond Lockton, Andrew W. Fitzgibbon
• Keywords: BMVC 2002, Computer Vision, Gesture, Gesture Recognition, Single-hand Gestures