Now showing items 1-4 of 4
P-N Learning: Bootstrapping Binary Classifiers by Structural Constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the label of one example restricts the labeling ...
Online learning of robust object detectors during unstable tracking
This work investigates the problem of robust, longterm visual tracking of unknown objects in unconstrained environments. It therefore must cope with frame-cuts, fast camera movements and partial/total object occlusions/d ...
Face-TLD: Tracking-Learning-Detection applied to faces
A novel system for long-term tracking of a human face in unconstrained videos is built on Tracking-Learning-Detection (TLD) approach. The system extends TLD with the concept of a generic detector and a validator which is ...
Forward-Backward Error: Automatic Detection of Tracking Failures
This paper proposes a novel method for tracking failure detection. The detection is based on the Forward-Backward error, i.e. the tracking is performed forward and backward in time and the discrepancies between these two ...