Abnormal Event Detection using Hypergraph based Multiple Objects Tracking Techniques in Surveillance Videos

dc.contributor.guide	Manivannan, D
dc.coverage.spatial	Computer Science
dc.creator.researcher	Palanivel, S
dc.date.accessioned	2025-03-17T04:52:48Z
dc.date.available	2025-03-17T04:52:48Z
dc.date.awarded	2024
dc.date.completed	2024
dc.date.registered	2016
dc.description.abstract	Abstract Included
dc.description.note	Ref p.158-165, App p.166-169
dc.format.accompanyingmaterial	DVD
dc.format.dimensions	30 cm
dc.format.extent	xvii, 169p
dc.identifier.researcherid
dc.identifier.uri	http://hdl.handle.net/10603/627697
dc.language	English
dc.publisher.institution	School of Computing
dc.publisher.place	Thanjavur
dc.publisher.university	SASTRA University
dc.relation	No.of References 103
dc.rights	university
dc.source.university	University
dc.subject.keyword	Artificial Neural Network, Context-free grammar, Rare event detection
dc.subject.keyword	Computer Science
dc.subject.keyword	Engineering and Technology
dc.subject.keyword	Hypergraph, Game-Theory, Video Anomaly Detection
dc.subject.keyword	Imaging Science and Photographic Technology
dc.subject.keyword	KAZE, SIFT, Optimization
dc.subject.keyword	Object matching, Hypergraph, Grid sampling
dc.subject.keyword	Streaming video monitoring, Object labeling
dc.title	Abnormal Event Detection using Hypergraph based Multiple Objects Tracking Techniques in Surveillance Videos
dc.title.alternative
dc.type.degree	Ph.D.

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