Learning generative models of scene features

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 1, Issue , 2001, Pages

  Sim, Robert ^a   Dudek, Gregory ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; IMAGE RECONSTRUCTION; LEARNING SYSTEMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; OBJECT RECOGNITION; POSITION CONTROL;

POSITION ESTIMATION;

FEATURE EXTRACTION;

EID: 0035680129     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. What is the set of images of an object under all possible lighting conditions
2. Using the condensation algorithm for robust, vision-based mobile robot localization
3. Robust place recognition using local appearance based methods
4. Object recognition from local scale-invariant features
5. Learning, positioning, and tracking visual appearance
6. Cross-validation of regression models
7. A network that learns to recognize 3d objects
8. Continuity properties of the appearance manifold for mobile robot position estimation
9. Multi-robot collaboration for robust exploration
10. A structured probabilistic model for recognition
11. Learning and evaluating visual features for pose estimation
12. Model-based brightness constraints: On direct estimation of structure and motion
13. A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping