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MVA
1990
162views Computer Vision» more  MVA 1990»
13 years 9 months ago
Map-Driven Image Interpretation by Associative Model Indexing
d at a high abstraction level, and consists in an expectation-driven search starting from symbolic object descriptions and using a version of a distributed blackboard system for re...
Gian Luca Foresti, Vittorio Murino, Carlo S. Regaz...
CRV
2011
IEEE
337views Robotics» more  CRV 2011»
12 years 8 months ago
Object Detection Using Principal Contour Fragments
Abstract—Contour features play an important role in object recognition. Psychological experiments have shown that maximum-curvature points are most distinctive along a contour [6...
Changhai Xu, Benjamin Kuipers
ICIP
2008
IEEE
14 years 10 months ago
Implicit spatial inference with sparse local features
This paper introduces a novel way to leverage the implicit geometry of sparse local features (e.g. SIFT operator) for the purposes of object detection and segmentation. A two-clas...
Deirdre O'Regan, Anil C. Kokaram
IJCV
2007
196views more  IJCV 2007»
13 years 8 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
2006
IEEE
14 years 10 months ago
Supervised Learning of Edges and Object Boundaries
Edge detection is one of the most studied problems in computer vision, yet it remains a very challenging task. It is difficult since often the decision for an edge cannot be made ...
Piotr Dollár, Zhuowen Tu, Serge Belongie