TY - GEN
T1 - Finding "unexplained" activities in video
AU - Albanese, Massimiliano
AU - Molinaro, Cristian
AU - Persia, Fabio
AU - Picariello, Antonio
AU - Subrahmanian, V. S.
PY - 2011
Y1 - 2011
N2 - Consider a video surveillance application that monitors some location. The application knows a set of activity models (that are either normal or abnormal or both), but in addition, the application wants to find video segments that are unexplained by any of the known activity models - these unexplained video segments may correspond to activities for which no previous activity model existed. In this paper, we formally define what it means for a given video segment to be unexplained (totally or partially) w.r.t. a given set of activity models and a probability threshold. We develop two algorithms - FindTUA and FindPUA - to identify Totally and Partially Unexplained Activities respectively, and show that both algorithms use important pruning methods. We report on experiments with a prototype implementation showing that the algorithms both run efficiently and are accurate.
AB - Consider a video surveillance application that monitors some location. The application knows a set of activity models (that are either normal or abnormal or both), but in addition, the application wants to find video segments that are unexplained by any of the known activity models - these unexplained video segments may correspond to activities for which no previous activity model existed. In this paper, we formally define what it means for a given video segment to be unexplained (totally or partially) w.r.t. a given set of activity models and a probability threshold. We develop two algorithms - FindTUA and FindPUA - to identify Totally and Partially Unexplained Activities respectively, and show that both algorithms use important pruning methods. We report on experiments with a prototype implementation showing that the algorithms both run efficiently and are accurate.
UR - http://www.scopus.com/inward/record.url?scp=84881051481&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881051481&partnerID=8YFLogxK
U2 - 10.5591/978-1-57735-516-8/IJCAI11-274
DO - 10.5591/978-1-57735-516-8/IJCAI11-274
M3 - Conference contribution
AN - SCOPUS:84881051481
SN - 9781577355120
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 1628
EP - 1634
BT - IJCAI 2011 - 22nd International Joint Conference on Artificial Intelligence
T2 - 22nd International Joint Conference on Artificial Intelligence, IJCAI 2011
Y2 - 16 July 2011 through 22 July 2011
ER -