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131
Voted
CVPR
2008
IEEE
16 years 5 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
131
Voted
OOPSLA
1989
Springer
15 years 7 months ago
Virtual Classes: A Powerful Mechanism in Object-Oriented Programming
The notions of class, subclass and virtual procedure are fairly well understood and recognized as some of the key concepts in object-oriented programming. The possibility of modif...
Ole Lehrmann Madsen, Birger Møller-Pedersen
140
Voted
CVPR
1996
IEEE
16 years 5 months ago
Combining greyvalue invariants with local constraints for object recognition
This paper addresses the problem of recognizing objects in large image databases. The method is based on local characteristics which are invariant to simzlarity transformations in...
Cordelia Schmid, Roger Mohr
150
Voted
ICCV
2007
IEEE
16 years 5 months ago
3D object recognition from range images using pyramid matching
Recognition of 3D objects from different viewpoints is a difficult problem. In this paper, we propose a new method to recognize 3D range images by matching local surface descripto...
Xinju Li, Igor Guskov
120
Voted
ICIP
2006
IEEE
16 years 5 months ago
Recognition of Multi-Object Events Using Attribute Grammars
* We present a method for representing and recognizing visual events using attribute grammars. In contrast to conventional grammars, attribute grammars are capable of describing fe...
Seong-Wook Joo, Rama Chellappa