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» Boosting Chain Learning for Object Detection
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ICASSP
2010
IEEE
13 years 7 months ago
Multi-View Object Detection by Classifier Interpolation
In this paper, we propose a novel solution for multi-view object detection. Given a set of training examples at different views, we select examples at a few key views and train on...
Xiaobai Liu, Haifeng Gong, Shuicheng Yan, Hai Jin
PAMI
2008
175views more  PAMI 2008»
13 years 7 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...
CVPR
2010
IEEE
13 years 7 months ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
IBPRIA
2007
Springer
14 years 1 months ago
Unidimensional Multiscale Local Features for Object Detection Under Rotation and Mild Occlusions
Abstract. In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the presen...
Michael Villamizar, Alberto Sanfeliu, Juan Andrade...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 10 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...