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CVPR
2004
IEEE
14 years 9 months ago
An Unsupervised, Online Learning Framework for Moving Object Detection
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
Vinod Nair, James J. Clark
ECCV
2008
Springer
14 years 9 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
CVPR
2001
IEEE
14 years 9 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones
CVPR
2010
IEEE
14 years 3 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
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