Spatio-activity based object detection

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dc.creatorSpringett, Jarrad
dc.creatorVendrig, Jeroen
dc.date2008-03-11
dc.date.accessioned2026-07-07T12:17:33Z
dc.date.available2026-07-07T12:17:33Z
dc.descriptionWe present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.
dc.descriptionTo be submitted to: AVSS 2008 conference
dc.identifierhttps://arxiv.org/abs/0803.1586
dc.identifierhttp://arxiv.org/abs/0803.1586
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/212114
dc.subjectComputer Vision and Pattern Recognition
dc.titleSpatio-activity based object detection
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