Part-Based Visual Tracking via Online Weighted P-N Learning

Figure 1

A flowchart in [17] to explain P-N learning. P-N learning algorithm initially develops a classifier from prior knowledge and then iterates over: (1) classify the unlabeled data and label it; (2) reclassify the samples within constrains and label them; (3) expand the training sample set; (4) retrain the classifier.