@conference {12723,
	title = {Adaptive visual tracking and recognition using particle filters},
	booktitle = {Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings. 2003 International Conference on},
	volume = {2},
	year = {2003},
	month = {2003/07//},
	pages = {II - 349-52 vol.2 - II - 349-52 vol.2},
	abstract = {This paper presents an improved method for simultaneous tracking and recognition of human faces from video, where a time series model is used to resolve the uncertainties in tracking and recognition. The improvements mainly arise from three aspects: (i) modeling the inter-frame appearance changes within the video sequence using an adaptive appearance model and an adaptive-velocity motion model; (ii) modeling the appearance changes between the video frames and gallery images by constructing intra- and extra-personal spaces; and (iii) utilization of the fact that the gallery images are in frontal views. By embedding them in a particle filter, we are able to achieve a stabilized tracker and an accurate recognizer when confronted by pose and illumination variations.},
	keywords = {adaptive, adaptive-velocity, appearance, extra-personal, Filtering, filters;, image, intra-personal, model;, MOTION, particle, processing;, recognition;, sequence;, sequences;, series, signal, spaces;, theory;, TIME, tracking;, video, visual},
	doi = {10.1109/ICME.2003.1221625},
	author = {Zhou,Shaohua and Chellapa, Rama and Moghaddam, B.}
}
