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» Visualizing Diversity and Depth over a Set of Objects
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ICML
2006
IEEE
16 years 2 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
ICRA
2008
IEEE
164views Robotics» more  ICRA 2008»
15 years 8 months ago
Visual servoing set free from image processing
— This paper proposes a new way to achieve robotic tasks by visual servoing. Instead of using geometric features (points, straight lines, pose, homography, etc.) as it is usually...
Christophe Collewet, Éric Marchand, Fran&cc...
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
14 years 10 months ago
Object Recognition with Hierarchical Kernel Descriptors
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
ICCV
2009
IEEE
16 years 7 months ago
Modeling Deformable Objects from a Single Depth Camera
We propose a novel approach to reconstruct complete 3D deformable models over time by a single depth camera, provided that most parts of the models are observed by the camera at...
Miao Liao, Qing Zhang, Huamin Wang, Ruigang Yang, ...
CVPR
2006
IEEE
15 years 8 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...