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» Learning Illumination Models While Tracking
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IJCV
2008
192views more  IJCV 2008»
13 years 8 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
IJCV
2010
158views more  IJCV 2010»
13 years 6 months ago
Metric Learning for Image Alignment
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
Minh Hoai Nguyen, Fernando De la Torre
CVPR
2008
IEEE
14 years 2 months ago
General Constraints for Batch Multiple-Target Tracking Applied to Large-Scale Videomicroscopy
While there is a large class of Multiple-Target Tracking (MTT) problems for which batch processing is possible and desirable, batch MTT remains relatively unexplored in comparis...
Kevin Smith, Alan Carleton, Vincent Lepetit
PAMI
2007
134views more  PAMI 2007»
13 years 8 months ago
Spatio-Temporal Context for Robust Multitarget Tracking
—In multitarget tracking, the main challenge is to maintain the correct identity of targets even under occlusions or when differences between the targets are small. The paper pro...
Hieu Tat Nguyen, Qiang Ji, Arnold W. M. Smeulders
CVIU
2008
179views more  CVIU 2008»
13 years 8 months ago
Incremental, scalable tracking of objects inter camera
This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated cameras with non overlapping fields of view. The approach relie...
Andrew Gilbert, Richard Bowden