Real-Time Tracking with On-line Feature Selection

@inproceedings{Grabner2006RealTimeTW,
  title={Real-Time Tracking with On-line Feature Selection},
  author={Michael Grabner and Helmut Grabner and Horst Bischof},
  year={2006}
}
The main idea is to formulate the tracking problem as a binary classification task and to achieve robustness by continuously updating the current classifier of the target object with respect to the current surrounding background. For this purpose we use an on-line AdaBoost feature selection algorithm [1] for tracking. The distinct advantage of the method is its capability of updating a model (classifier) during tracking. This allows on the one hand that a classifier can adapt to any object and… CONTINUE READING