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Dynamic texture recognition using local binary patterns with an application to facial expressions.

Zhao G, Pietikäinen M

Machine Vision Group, Department of Electrical and Information Engineering, University of Oulu, FI-90014 Oulu, Finland. gyzhao@ee.oulu.fi

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Published 13 April 2007 in IEEE Trans Pattern Anal Mach Intell, 29(6): 915-28.
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Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)

Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)