Face tracking in low resolution videos under illumination variations

TitleFace tracking in low resolution videos under illumination variations
Publication TypeConference Papers
Year of Publication2011
AuthorsZou WWW, Chellappa R, Yuen PC
Conference Name2011 18th IEEE International Conference on Image Processing (ICIP)
Date Published2011/09/11/14
ISBN Number978-1-4577-1304-0
KeywordsAdaptation models, Computational modeling, Face, face recognition, face tracking, GLF-based tracker, gradient methods, gradient-logarithmic field feature, illumination variations, lighting, low resolution videos, low-resolution, particle filter, particle filter framework, particle filtering (numerical methods), Robustness, tracking, video signal processing, Videos, Visual face tracking

In practical face tracking applications, the face region is often small and affected by illumination variations. We address this problem by using a new feature, namely the Gradient-Logarithmic Field (GLF) feature, in the particle filter framework. The GLF feature is robust under illumination variations and the GLF-based tracker does not assume any model for the face being tracked and is effective in low-resolution video. Experimental results show that the proposed GFL-based tracker works well under significant illumination changes and outperforms some of the state-of-the-art algorithms.