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IWCM
2004
Springer
13 years 11 months ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
ICCV
2009
IEEE
2061views Computer Vision» more  ICCV 2009»
14 years 11 months ago
Background Subtraction for Freely Moving Cameras
Background subtraction algorithms define the background as parts of a scene that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving obj...
Yaser Sheikh, Omar Javed, Takeo Kanade
TCSV
2008
291views more  TCSV 2008»
13 years 6 months ago
A Statistical Video Content Recognition Method Using Invariant Features on Object Trajectories
Abstract--This work is dedicated to a statistical trajectorybased approach addressing two issues related to dynamic video content understanding: recognition of events and detection...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
ICIP
2006
IEEE
14 years 8 months ago
Estimation of Dynamic Background for Fluorescence Video-Microscopy
This paper describes a method for separating moving objects from temporally varying background in time-lapse confocal microscopy image sequences representing fluorescently tagged ...
Charles Kervrann, Jérôme Boulanger, P...
WACV
2005
IEEE
13 years 11 months ago
Persistent Objects Tracking Across Multiple Non Overlapping Cameras
We present an approach for persistent tracking of moving objects observed by non-overlapping and moving cameras. Our approach robustly recovers the geometry of non-overlapping vie...
Jinman Kang, Isaac Cohen, Gérard G. Medioni