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» The Dark Side of Object Learning: Learning Objects
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3DPVT
2006
IEEE
247views Visualization» more  3DPVT 2006»
14 years 1 months ago
Contour-Based Object Detection in Range Images
This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extracti...
Stefan Stiene, Kai Lingemann, Andreas Nüchter...
ACSW
2004
13 years 10 months ago
Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...
William D. Smart, Mengjie Zhang
IJCV
2000
136views more  IJCV 2000»
13 years 9 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
13 years 5 months ago
Object Recognition with Hierarchical Kernel Descriptors
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
CVPR
2012
IEEE
11 years 11 months ago
Meta-class features for large-scale object categorization on a budget
In this paper we introduce a novel image descriptor enabling accurate object categorization even with linear models. Akin to the popular attribute descriptors, our feature vector ...
Alessandro Bergamo, Lorenzo Torresani