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» Object Classification in Visual Surveillance Using Adaboost
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ECCV
2006
Springer
15 years 5 months ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson
MICCAI
2002
Springer
16 years 2 months ago
Performance Issues in Shape Classification
Shape comparisons of two groups of objects often have two goals: to create a classifier to separate the groups and to provide information that shows differences between classes. We...
Samson J. Timoner, Polina Golland, Ron Kikinis, Ma...
TRS
2008
15 years 1 months ago
The Neurophysiological Bases of Cognitive Computation Using Rough Set Theory
A popular view is that the brain works in a similar way to a digital computer or a Universal Turing Machine by processing symbols. Psychophysical experiments and our amazing capabi...
Andrzej W. Przybyszewski
CVPR
2007
IEEE
16 years 3 months ago
Principal Curvature-Based Region Detector for Object Recognition
This paper presents a new structure-based interest region detector called Principal Curvature-Based Regions (PCBR) which we use for object class recognition. The PCBR interest ope...
Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas ...
PAMI
2006
185views more  PAMI 2006»
15 years 1 months ago
Generic Object Recognition with Boosting
This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...