@conference {12484,
	title = {Group motion segmentation using a Spatio-Temporal Driving Force Model},
	booktitle = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on},
	year = {2010},
	month = {2010/06//},
	pages = {2038 - 2045},
	abstract = {We consider the {\textquoteleft}group motion segmentation{\textquoteright} problem and provide a solution for it. The group motion segmentation problem aims at analyzing motion trajectories of multiple objects in video and finding among them the ones involved in a {\textquoteleft}group motion pattern{\textquoteright}. This problem is motivated by and serves as the basis for the {\textquoteleft}multi-object activity recognition{\textquoteright} problem, which is currently an active research topic in event analysis and activity recognition. Specifically, we learn a Spatio-Temporal Driving Force Model to characterize a group motion pattern and design an approach for segmenting the group motion. We illustrate the approach using videos of American football plays, where we identify the offensive players, who follow an offensive motion pattern, from motions of all players in the field. Experiments using GaTech Football Play Dataset validate the effectiveness of the segmentation algorithm.},
	keywords = {activity, American, analysis;image, dataset;group, driving, football, force, model;image, MOTION, pattern;group, play, plays;GaTech, problem;spatiotemporal, recognition, recognition;image, segmentation;, segmentation;motion, trajectories;multiobject},
	doi = {10.1109/CVPR.2010.5539880},
	author = {Ruonan Li and Chellapa, Rama}
}
