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CVPR
2008
IEEE
14 years 7 months ago
Semi-supervised boosting using visual similarity learning
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Christian Leistner, Helmut Grabner, Horst Bischof
DAGM
2009
Springer
13 years 11 months ago
Active Structured Learning for High-Speed Object Detection
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Christoph H. Lampert, Jan Peters
ICCV
2003
IEEE
14 years 7 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann
ICCV
2007
IEEE
14 years 7 months ago
A Scalable Approach to Activity Recognition based on Object Use
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where m...
Jianxin Wu, Adebola Osuntogun, Tanzeem Choudhury, ...
CVPR
2009
IEEE
1453views Computer Vision» more  CVPR 2009»
14 years 9 months ago
Learning Photometric Invariance From Diversified Color Model Ensembles
Color is a powerful visual cue for many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the i...
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez