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» Robot Localization Using a Computer Vision Sextant
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CVPR
2012
IEEE
13 years 5 months ago
A data driven method for feature transformation
Most image understanding algorithms begin with the extraction of information thought to be relevant to the particular task. This is commonly known as feature extraction and has, u...
Mert Dikmen, Derek Hoiem, Thomas S. Huang
EMMCVPR
2001
Springer
15 years 7 months ago
A Hierarchical Markov Random Field Model for Figure-Ground Segregation
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Stella X. Yu, Tai Sing Lee, Takeo Kanade
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
15 years 5 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ICRA
2009
IEEE
149views Robotics» more  ICRA 2009»
15 years 9 months ago
On achievable accuracy for pose tracking
Abstract—This paper presents Cramér-Rao bound-like inequalities for pose tracking, which is defined as the problem of recovering the robot displacement given two successive rea...
Andrea Censi
ICRA
2008
IEEE
197views Robotics» more  ICRA 2008»
15 years 9 months ago
A Bayesian framework for optimal motion planning with uncertainty
— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...