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TIP
2008
344views more  TIP 2008»
13 years 7 months ago
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being...
Lucia Maddalena, Alfredo Petrosino
ICCV
2007
IEEE
14 years 9 months ago
Learning to Find Object Boundaries Using Motion Cues
While great strides have been made in detecting and localizing specific objects in natural images, the bottom-up segmentation of unknown, generic objects remains a difficult chall...
Andrew N. Stein, Derek Hoiem, Martial Hebert
ICCV
2001
IEEE
14 years 9 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
TOG
2008
196views more  TOG 2008»
13 years 7 months ago
Motion-invariant photography
Object motion during camera exposure often leads to noticeable blurring artifacts. Proper elimination of this blur is challenging because the blur kernel is unknown, varies over t...
Anat Levin, Peter Sand, Taeg Sang Cho, Fréd...
ISVC
2005
Springer
14 years 1 months ago
Background Updating for Visual Surveillance
Scene changes such as moved objects, parked vehicles, or opened/closed doors need to be carefully handled so that interesting foreground targets can be detected along with the shor...
Kyungnam Kim, David Harwood, Larry S. Davis