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Spatiotemporal approach for tracking using rough entropy and frame subtraction

Uma Shankar, B.; Chakraborty, Debarati

Authors

B. Uma Shankar

Debarati Chakraborty



Abstract

We present here an approach for video image segmentation where spatial segmentation is based on rough sets and granular computing and temporal segmentation is done by consecutive frame subtraction. Then the intersection of the temporal segmentation and spatial segmentation for the same frame is analyzed in RGB feature space. The estimated statistics of the intersecting regions is used for the object reconstruction and tracking. © 2011 Springer-Verlag Berlin Heidelberg.

Citation

Uma Shankar, B., & Chakraborty, D. (2011). Spatiotemporal approach for tracking using rough entropy and frame subtraction. Lecture notes in computer science, 6744 LNCS, 193-199. https://doi.org/10.1007/978-3-642-21786-9_33

Presentation Conference Type Conference Paper (published)
Acceptance Date Apr 4, 2011
Publication Date Jul 14, 2011
Deposit Date Mar 13, 2024
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 6744 LNCS
Pages 193-199
ISBN 9783642217852
DOI https://doi.org/10.1007/978-3-642-21786-9_33
Keywords Turbo-expander; Solar; Low-temperature; Performance evaluation
Public URL https://hull-repository.worktribe.com/output/4589093