The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent the actions as a sequence of temporal isolated instances, denoted primitives. These primitives are each defined by four features extracted from motion images. The primitives are recognized in each frame based on a trained classifier resulting in a sequence of primitives. From this sequence we recognize different temporal actions using a probabilistic Edit Distance method. The method is tested on different actions with and without noise and the results show recognizing rates of 88.7% and 85.5%, respectively.
|Status||Udgivet - 2006|
|Begivenhed||The 15th Danish conference on pattern recognition and image analysis - Copenhagen, Danmark|
Varighed: 24 aug. 2006 → 25 aug. 2006
Konferencens nummer: 15
|Konference||The 15th Danish conference on pattern recognition and image analysis|
|Periode||24/08/2006 → 25/08/2006|