Online Discriminative Tracking With Active Example Selection.

Most existing discriminative tracking algorithms use a sampling-and-labeling strategy to collect examples and treat the training example collection as a task that is independent of classifier learning. However, the examples collected directly by sampling are neither necessarily informative nor intended to be useful for classifier learning. Updating the classifier with these examples might introduc...