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» Learning Depth from Stereo
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CVPR
2007
IEEE
14 years 9 months ago
Learning Conditional Random Fields for Stereo
State-of-the-art stereo vision algorithms utilize color changes as important cues for object boundaries. Most methods impose heuristic restrictions or priors on disparities, for e...
Daniel Scharstein, Chris Pal
GRAPHITE
2005
ACM
14 years 1 months ago
Drawing the real
In this paper we present an algorithm to automatically produce artistic drawings from stereo image pairs. The input to the algorithm is a natural scene, along with a user-defined...
Danijela Markovic, Margrit Gelautz
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
14 years 2 months ago
Probabilistic categorization of kitchen objects in table settings with a composite sensor
— In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our fra...
Zoltan Csaba Marton, Radu Bogdan Rusu, Dominik Jai...
CVPR
2007
IEEE
14 years 9 months ago
Layered Depth Panoramas
Representations for interactive photorealistic visualization of scenes range from compact 2D panoramas to dataintensive 4D light fields. In this paper, we propose a technique for ...
Ke Colin Zheng, Sing Bing Kang, Michael F. Cohen, ...
ICPR
2002
IEEE
14 years 8 months ago
Stereo Tracking Using ICP and Normal Flow Constraint
This paper presents a new approach for 3D view registration of stereo images. We introduce a hybrid error function which combines constraints from the ICP (Iterative Closest Point...
Louis-Philippe Morency, Trevor Darrell