RECOGNITION OF PARTLY OCCLUDED PERSON ACTIONS IN MEETING SCENARIOS (MA-P3)

Author(s) : Martin Zobl (Munich University of Technology, Institute for human-machine communication, Germany) Andreas Laika (Munich University of Technology, Institute for human-machine communication, Germany) Frank Wallhoff (Munich University of Technology, Institute for human-machine communication, Germany) Gerhard Rigoll (Munich University of Technology, Institute for human-machine communication, Germany)

Abstract : This proposal describes a novel approach for handling partly occluded gestures in the feature domain with gesture specific Kalman-Filters. An estimation of the Kalman-Filter parameters using artificial neural networks is introduced. The approach is demonstrated and evaluated on data from a meeting scenario and can be generalized to all gesture based problems concerning partial occlusions.

Menu