The BEHAVE video dataset: ground truthed video for multi-person behavior classification

Although there is much research on behaviour recognition in time-varying video, there are few ground truthed datasets for assessing multi-person behavioral interactions. This short paper presents the BEHAVE project’s dataset, which has around 90,000 frames of humans identified by bounding boxes, with interacting groups classified into one of 5 different behaviors. An example of its use is also presented.

[1]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[2]  Seth Bullock,et al.  Simple Heuristics That Make Us Smart , 1999 .

[3]  Aaron F. Bobick,et al.  A Framework for Recognizing Multi-Agent Action from Visual Evidence , 1999, AAAI/IAAI.

[4]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[5]  Alex Pentland,et al.  A Bayesian Computer Vision System for Modeling Human Interactions , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Hilary Buxton,et al.  Learning and understanding dynamic scene activity: a review , 2003, Image Vis. Comput..

[7]  Barbara Caputo,et al.  Recognizing human actions: a local SVM approach , 2004, ICPR 2004.

[8]  Robert B. Fisher,et al.  The PETS04 Surveillance Ground-Truth Data Sets , 2004 .

[9]  Hanna M. Wallach,et al.  Conditional Random Fields: An Introduction , 2004 .

[10]  T. List,et al.  Performance evaluating the evaluator , 2005, 2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance.

[11]  Bob Fisher,et al.  Recognition of coordinated multi agent activities, the individual vs the group , 2006 .

[12]  Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships , 2006 .

[13]  M. Shah,et al.  Object tracking: A survey , 2006, CSUR.

[14]  Mubarak Shah,et al.  Learning, detection and representation of multi-agent events in videos , 2007, Artif. Intell..

[15]  Robert B. Fisher,et al.  Non Parametric Classification of Human Interaction , 2007, IbPRIA.

[16]  François Brémond,et al.  ETISEO, performance evaluation for video surveillance systems , 2007, 2007 IEEE Conference on Advanced Video and Signal Based Surveillance.

[17]  Tim J. Ellis,et al.  ViHASi: Virtual human action silhouette data for the performance evaluation of silhouette-based action recognition methods , 2008, 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras.

[18]  Matej Kristan,et al.  A trajectory-based analysis of coordinated team activity in a basketball game , 2009, Comput. Vis. Image Underst..