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» Learning Models for Object Recognition
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PR
2007
96views more  PR 2007»
13 years 9 months ago
Weighted and robust learning of subspace representations
A reliable system for visual learning and recognition should enable a selective treatment of individual parts of input data and should successfully deal with noise and occlusions....
Danijel Skocaj, Ales Leonardis, Horst Bischof
ICPR
2008
IEEE
14 years 4 months ago
Flexible object recognition in cluttered scenes using relative point distribution models
This paper introduces an edge-based object recognition method that is robust with respect to clutter, occlusion and object deformations. The method combines the use of local featu...
Alexandros Bouganis, Murray Shanahan
CORR
2010
Springer
108views Education» more  CORR 2010»
13 years 7 months ago
Affine Invariant, Model-Based Object Recognition Using Robust Metrics and Bayesian Statistics
We revisit the problem of model-based object recognition for intensity images and attempt to address some of the shortcomings of existing Bayesian methods, such as unsuitable prior...
Vasileios Zografos, Bernard F. Buxton
PAMI
2006
196views more  PAMI 2006»
13 years 10 months ago
Three-Dimensional Model-Based Object Recognition and Segmentation in Cluttered Scenes
Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based alg...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
ICPR
2000
IEEE
14 years 1 months ago
Recognition of Indoor Images Employing Qualitative Model Fitting and Supporting Relation between Objects
In this paper, we describe a new design of a recognition system for a single image of indoor scene including complex occlusions. In our system, rst, the system estimates 3D struc...
Keiji Yanai, Koichiro Deguchi