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» Multiple Component Learning for Object Detection
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CVPR
2001
IEEE
15 years 11 months ago
Learning Models for Object Recognition
We consider learning models for object recognition from examples. Our method is motivated by systems that use the Hausdorff distance as a shape comparison measure. Typically an ob...
Pedro F. Felzenszwalb
ACCV
2006
Springer
15 years 3 months ago
Boosted Algorithms for Visual Object Detection on Graphics Processing Units
Nowadays, the use of machine learning methods for visual object detection has become widespread. Those methods are robust. They require an important processing power and a high mem...
Hicham Ghorayeb, Bruno Steux, Claude Laurgeau
IJCV
2000
136views more  IJCV 2000»
14 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
ICANN
2009
Springer
15 years 4 months ago
Multimodal Sparse Features for Object Detection
In this paper the sparse coding principle is employed for the representation of multimodal image data, i.e. image intensity and range. We estimate an image basis for frontal face i...
Martin Haker, Thomas Martinetz, Erhardt Barth
CVPR
2007
IEEE
15 years 11 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...