@conference {12444,
	title = {Face tracking in low resolution videos under illumination variations},
	booktitle = {2011 18th IEEE International Conference on Image Processing (ICIP)},
	year = {2011},
	month = {2011/09/11/14},
	pages = {781 - 784},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {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.},
	keywords = {Adaptation 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},
	isbn = {978-1-4577-1304-0},
	doi = {10.1109/ICIP.2011.6116672},
	author = {Zou, W.W.W. and Chellapa, Rama and Yuen, P.C.}
}
