TY - GEN
T1 - Using probabilistic ontologies for video exploration
AU - Bustamante, Miguel A.
AU - Corso, Jason J.
PY - 2012
Y1 - 2012
N2 - Video data is being collected at alarming rates and yet there exists no comprehensive forensic toolset that enables the analyst to quickly examine video in the context of the massive collections. This research builds a System that studies video at a semantic level by means of a joint solution to semantic entity extraction, entity-entity relationship extraction, and dynamic event recognition. The working of the System is grounded in formal ontology. This ontology is jointly induced from the data and established by the human domain experts (i.e., interactive machine learning). Specifically, we implement a Multi Entity Bayesian Network (a form of a probabilistic ontology); we test our System on two-on-two basketball game videos, and our results demonstrate state of the art detection rates on activities like passing the ball, and shooting, consequently promising that the presented methodology is an encouraging direction for semantically rich video analysis.
AB - Video data is being collected at alarming rates and yet there exists no comprehensive forensic toolset that enables the analyst to quickly examine video in the context of the massive collections. This research builds a System that studies video at a semantic level by means of a joint solution to semantic entity extraction, entity-entity relationship extraction, and dynamic event recognition. The working of the System is grounded in formal ontology. This ontology is jointly induced from the data and established by the human domain experts (i.e., interactive machine learning). Specifically, we implement a Multi Entity Bayesian Network (a form of a probabilistic ontology); we test our System on two-on-two basketball game videos, and our results demonstrate state of the art detection rates on activities like passing the ball, and shooting, consequently promising that the presented methodology is an encouraging direction for semantically rich video analysis.
KW - Multi entity bayesian network
KW - Ontology
KW - Probabilistic ontology
KW - Video semantic analyses
UR - http://www.scopus.com/inward/record.url?scp=84877887095&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877887095&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84877887095
SN - 9781622768271
T3 - 18th Americas Conference on Information Systems 2012, AMCIS 2012
SP - 1335
EP - 1348
BT - 18th Americas Conference on Information Systems 2012, AMCIS 2012
T2 - 18th Americas Conference on Information Systems 2012, AMCIS 2012
Y2 - 9 August 2012 through 12 August 2012
ER -