Detecting group activities using rigidity of formation

Most work in human activity recognition is limited to relatively simple behaviors like sitting down, standing up or other dramatic posture changes. Very little has been achieved in detecting more complicated behaviors especially those characterized by the collective participation of several individuals. In this work we present a novel approach to recognizing the class of activities characterized by their rigidity in formation for example people parades, airplane flight formations or herds of animals. The central idea is to model the entire group as a collective rather than focusing on each individual separately. We model the formation as a 3D polygon with each corner representing a participating entity. Tracks from the entities are treated as tracks of feature points on the 3D polygon. Based on the rank of the track matrix we can determine if the 3D polygon under consideration behaves rigidly or undergoes non-rigid deformation. Our method is invariant to camera motion and does not re...

• Type: Conference
• Year: 2005
• Where: MM
• Authors: Saad M. Khan, Mubarak Shah
• Keywords: Activity Recognition, Dramatic Posture Changes, Human Activity Recognition, MM 2005