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» Discovering Operators and Features for Object Detection
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ICCV
2005
IEEE
15 years 3 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
CVPR
2001
IEEE
16 years 3 days ago
Tracking of Object with SVM Regression
This paper presents a novel feature-matching based approach for rigid object tracking. The proposed method models the tracking problem as discovering the affine transforms of obje...
Weiyu Zhu, Song Wang, Ruei-Sung Lin, Stephen E. Le...
99
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KAIS
2007
120views more  KAIS 2007»
14 years 10 months ago
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Abstract. Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some importa...
Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, David W...
3DPVT
2006
IEEE
187views Visualization» more  3DPVT 2006»
15 years 1 months ago
Linking Feature Lines on 3D Triangle Meshes with Artificial Potential Fields
We propose artificial potential fields as a support theory for a feature linking algorithm. This algorithm operates on 3D triangle meshes derived from multiple range scans of an o...
David L. Page, Andreas Koschan, Mongi A. Abidi
AAAI
2008
15 years 12 days ago
Markov Blanket Feature Selection for Support Vector Machines
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Jianqiang Shen, Lida Li, Weng-Keen Wong