%0 Conference Paper %B International Joint Conference on Artificial Intelligence %D 2007 %T Detecting stochastically scheduled activities in video %A Albanese, M. %A Moscato, V. %A Picariello, A. %A V.S. Subrahmanian %A Udrea,O. %X The ability to automatically detect activities invideo is of increasing importance in applications such as bank security, airport tarmac security, bag- gage area security and building site surveillance. We present a stochastic activity model composed of atomic actions which are directly observable through image understanding primitives. We focus on answering two types of questions: (i) what are the minimal sub-videos in which a given action is identified with probability above a certain thresh- old and (ii) for a given video, can we decide which activity from a given set most likely occurred? We provide the MPS algorithm for the first problem, as well as two different algorithms (naiveMPA and MPA) to solve the second. Our experimental re- sults on a dataset consisting of staged bank robbery videos (described in [Vu et al., 2003]) show that our algorithms are both fast and provide high qual- ity results when compared to human reviewers. %B International Joint Conference on Artificial Intelligence %P 1802 - 1807 %8 2007/// %G eng