Social Signal Processing aims at analyzing and modeling social signals in human–human and human–machine interactions. Non-verbal behavior, including gaze, facial expression and body language, is extremely significant in human interaction and can be captured by means of computer vision techniques. In the group behavior analysis some key variables are the proximity and focus of attention indicating the object or person one is attending to.
CocktailParty Dataset is a multi-view dataset designed for social behavior analysis.
Disclaimer: CocktailParty dataset can be used for research or academic purposes only. The dataset has been published along with the paper referenced below.
note on usage
Although the data-set is multi-view, some groups working on single-view approaches have used only CAM1 data for their results (e.g. as we did in our ICCV15 paper cited below).
E. Ricci, J. Varadarajan, R. Subramanian, S. Rota Bulò, N. Ahuja, O. Lanz: Uncovering Interactions and Interactors: Joint Estimation of Head, Body Orientation and F-formations from Surveillance Video. International Conference on Computer Vision - ICCV, Santiago, Chile, December 13-16, 2015
R. Subramanian, Y. Yan, J. Staiano, O. Lanz, N. Sebe: On the relationship between head pose, social attention and personality prediction for unstructured and dynamic group interactions. ACM International Conference on Multimodal Interaction - ICMI, Sydney, Australia, December 9-13, 2013
F. Setti, O. Lanz, R. Ferrario, V. Murino, M. Cristani: Multi-scale f-formation discovery for group detection. IEEE International Conference on Image Processing - ICIP, Melbourne, Australia, 13-18 September 2013
G. Zen, B. Lepri, E. Ricci, O. Lanz: Space Speaks - Towards Socially and Personality Aware Visual Surveillance. Multimodal Pervasive Video Analysis Workshop - MPVA 2010, Satellite workshop of ACMMM 2010, Firenze, Italy, October 29, 2010, pp. 37-42