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IJCV
2007
196views more  IJCV 2007»
14 years 9 months ago
Weakly Supervised Scale-Invariant Learning of Models for Visual Recognition
We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2004
IEEE
15 years 11 months ago
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
Fu Jie Huang, Léon Bottou, Yann LeCun
97
Voted
3DIM
1999
IEEE
15 years 1 months ago
Large Data Sets and Confusing Scenes in 3-D Surface Matching and Recognition
In this paper, we report on recent extensions to a surface matching algorithm based on local 3-D signatures. This algorithm was previously shown to be effective in view registrati...
Owen T. Carmichael, Daniel F. Huber, Martial Heber...
79
Voted
RAS
2007
85views more  RAS 2007»
14 years 9 months ago
Self-localization in non-stationary environments using omni-directional vision
This paper presents an image-based approach for localization in non-static environments using local feature descriptors, and its experimental evaluation in a large, dynamic, popul...
Henrik Andreasson, André Treptow, Tom Ducke...
ICRA
2008
IEEE
204views Robotics» more  ICRA 2008»
15 years 4 months ago
Active exploration and keypoint clustering for object recognition
— Object recognition is a challenging problem for artificial systems. This is especially true for objects that are placed in cluttered and uncontrolled environments. To challenge...
Gert Kootstra, Jelmer Ypma, Bart de Boer