on-line boosting for tracking

Real-time Tracking via On-line Boosting

H. Grabner, M. Grabner, and H. Bischof.
In Proceedings British Machine Vision Conference (BMVC), volume 1, pages 47-56, 2006


On-line Boosting and Vision
H. Grabner, and H. Bischof
In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 260-267, 2006


Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which implies that all training data has to be a priori given; training and usage of the classifier are separate steps. Training the classifier on-line and incrementally as new data becomes available has several advantages and opens new areas of application for boosting in computer vision. In this paper we propose a novel on-line AdaBoost feature selection method. In conjunction with efficient feature extraction methods the method is real time capable. We demonstrate the multifariousness of the method on such diverse tasks as learning complex background models, visual tracking and object detection. All approaches benefit significantly by the on-line training.


Tracking Sylvester

Tracking David
Tracking Shrek

Tracking a glass

Tracking a glass under occlusion

Tracking failure in case of a partial occlusion which is slowly integrated into the object model