Spatiotemporal approach for tracking using rough entropy and frame subtraction

Uma Shankar, B.; Chakraborty, Debarati

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. Spatiotemporal approach for tracking using rough entropy and frame subtraction

• 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
• 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