Title

Detecting Group Activities Using Rigidity Of Formation

Keywords

Rank Constraint; Rigid Formations; Structure from Motion

Abstract

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 require an a priori model or a training phase. Copyright © 2005 ACM.

Publication Date

12-1-2005

Publication Title

Proceedings of the 13th ACM International Conference on Multimedia, MM 2005

Number of Pages

403-406

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/1101149.1101237

Socpus ID

84883082511 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84883082511

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