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» Statistical Models of Appearance for Computer Vision
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122
Voted
CVPR
2012
IEEE
13 years 6 months ago
Improving multi-target tracking via social grouping
We address the problem of multi-person dataassociation-based tracking (DAT) in semi-crowded environments from a single camera. Existing trackletassociation-based methods using pur...
Zhen Qin, Christian R. Shelton
155
Voted
CVPR
2012
IEEE
13 years 6 months ago
RGB-(D) scene labeling: Features and algorithms
Scene labeling research has mostly focused on outdoor scenes, leaving the harder case of indoor scenes poorly understood. Microsoft Kinect dramatically changed the landscape, show...
Xiaofeng Ren, Liefeng Bo, Dieter Fox
152
Voted
CVPR
2007
IEEE
16 years 5 months ago
Topology Preserving Log-Unbiased Nonlinear Image Registration: Theory and Implementation
In this paper, we present a novel framework for constructing large deformation log-unbiased image registration models that generate theoretically and intuitively correct deformati...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...
131
Voted
CVPR
1996
IEEE
16 years 5 months ago
MUSE: Robust Surface Fitting using Unbiased Scale Estimates
Despite many successful applications of robust statistics, they have yet to be completely adapted to many computer vision problems. Range reconstruction, particularly in unstructu...
James V. Miller, Charles V. Stewart
137
Voted
CVPR
2010
IEEE
16 years 5 days ago
The Role of Features, Algorithms and Data in Visual Recognition
There are many computer vision algorithms developed for visual (scene and object) recognition. Some systems focus on involved learning algorithms, some leverage millions of trainin...
Devi Parikh and C. Lawrence Zitnick