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» Object Classification in Visual Surveillance Using Adaboost
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CVPR
2008
IEEE
16 years 3 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
ICCV
2009
IEEE
14 years 11 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
ICIP
2005
IEEE
16 years 2 months ago
Robust tracking with motion estimation and kernel-based color modelling
Visual tracking is still a challenging problem in computer vision. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. I...
Patrick Bouthemy, Patrick Pérez, R. Venkate...
ICCV
2003
IEEE
16 years 3 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
MVA
2011
336views Computer Vision» more  MVA 2011»
14 years 8 months ago
In-vehicle camera traffic sign detection and recognition
: In this paper we discuss theoretical foundations and a practical realization of a real-time traffic sign detection, tracking and recognition system operating on board of a vehicl...
Andrzej Ruta, Fatih Porikli, Shintaro Watanabe, Yo...