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» A Framework for Visual Servoing
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159
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CVPR
2009
IEEE
16 years 10 months ago
LidarBoost: Depth Superresolution for ToF 3D Shape Scanning
Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is v...
Sebastian Schuon (Stanford University), Christian ...
117
Voted
CVPR
2009
IEEE
1084views Computer Vision» more  CVPR 2009»
16 years 10 months ago
Describing Objects by their Attributes
We propose to shift the goal of recognition from naming to describing. Doing so allows us not only to name familiar objects, but also: to report unusual aspects of a familiar ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
173
Voted
CVPR
2009
IEEE
16 years 10 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
138
Voted
CVPR
2003
IEEE
16 years 5 months ago
Polydioptric Camera Design and 3D Motion Estimation
Most cameras used in computer vision applications are still based on the pinhole principle inspired by our own eyes. It has been found though that this is not necessarily the opti...
Cornelia Fermüller, Jan Neumann, Yiannis Aloi...
149
Voted
CVPR
2005
IEEE
16 years 5 months ago
Digital Tapestry
This paper addresses the novel problem of automatically synthesizing an output image from a large collection of different input images. The synthesized image, called a digital tap...
Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,...