PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Face-TLD: Tracking-Learning-Detection Applied to Faces
Zdenek Kálal, Krystian Mikolajczyk and Jiri Matas
International Conference on Image Processing 2010.

Abstract

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 designed for real-time face tracking resistent to occlusions and appearance changes. The off-line trained detector localizes frontal faces and the online trained validator decides which faces correspond to the tracked subject. Several strategies for building the validator during tracking are quantitatively evaluated. The system is validated on a sitcom episode (23 min.) and a surveillance (8 min.) video. In both cases the system detects-tracks the face and automatically learns a multi-view model from a single frontal example and an unlabeled video.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:6982
Deposited By:Zdenek Kálal
Deposited On:05 August 2010