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» Learning Image Components for Object Recognition
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CVPR
2007
IEEE
16 years 5 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
CVPR
2012
IEEE
13 years 5 months ago
Semantic structure from motion with points, regions, and objects
Structure from motion (SFM) aims at jointly recovering the structure of a scene as a collection of 3D points and estimating the camera poses from a number of input images. In this...
Sid Ying-Ze Bao, Mohit Bagra, Yu-Wei Chao, Silvio ...
ICPR
2006
IEEE
16 years 4 months ago
Object and Scene Classification: what does a Supervised Approach Provide us?
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...
CVPR
1997
IEEE
16 years 5 months ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
DAGM
2005
Springer
15 years 8 months ago
Vision-Based 3D Object Localization Using Probabilistic Models of Appearance
The ability to accurately localize objects in an observed scene is regarded as an important precondition for many practical applications including automatic manufacturing, quality ...
Christian Plagemann, Thomas Müller, Wolfram B...