The dataset serves for checking the ability in detecting social interactions, i.e., people that talk with themselves.
The dataset represents a coffee-break scenario of a social event that lasted 4 days, captured by two cameras. The dataset is part of a social signaling project whose aim is to monitor how social relations evolve over time. Nowadays, only 2 sequences of a single day of a single camera have been annotated (but novel sequences are going to appear, keep in touch!). A psychologist annotated the videos indicating the groups present in the scenes, for a total of 45 frames for Seq1 and 75 frames for Seq2. The annotations have been done by analyzing each frame and a set of questionnaires that the subjects filled in. The dataset is still challenging from the tracking and head pose estimation point of view, due to multiple occlusions. Results of this dataset have been published in the referenced paper.
[Coffeebreak Dataset] - Details
The dataset includes
the calibration parameters to project points on the ground plane
the original frames
the output of the tracker, i.e., trajectories for several people
the head orientation results
the ground truth, i.e., the (tracked) people that interact in F-formations
To obtain this dataset, send an email to Pavistech and to Marco Cristani, indicating as subject [CoffeeBreak dataset]. If you want, I can send you also the synthetic data employed in the referenced papaer. Note that the dataset is available only for research purposes.
[Coffeebreak Dataset] - References
 M. Cristani, L. Bazzani, G. Paggetti, A. Fossati, A. Del Bue, G. Menegaz, V. Murino, Social interaction discovery by statistical analysis of F-formations, British Machine Vision Conference, (BMVC), 2011