By the same authors

Facial Expression Recognition Using Nonrigid Motion Parameters and Shape-from-Shading

Research output: Chapter in Book/Report/Conference proceedingConference contribution



Publication details

Title of host publicationComputer Analysis of Images and Patterns - 14th International Conference, CAIP 2011, Seville, Spain, August 29-31, 2011, Proceedings, Part II
DatePublished - 2011
Number of pages9
Place of PublicationBERLIN
EditorsPedro Real, Daniel Díaz-Pernil, Helena Molina-Abril, Ainhoa Berciano, Walter G. Kropatsch
EditionPART 2
Original languageEnglish
ISBN (Print)978-3-642-23678-5

Publication series

NameLecture Notes in Computer Science


This paper presents a 3D motion based approach to facial expression recognition from video sequences. A non-Lambertian shape-from-shading (SFS) framework is used to recover 3D facial surfaces. The SFS technique avoids heavy computational requirements normally encountered by using a 3D face model. Then, a parametric motion model and optical flow are employed to obtain the nonrigid motion parameters of surface patches. At first, we obtain uniform motion parameters under the assumptions that motion due to change in expressions is temporally consistent. Then we relax the uniform motion constraint, and obtain temporal motion parameters. The two types of motion parameters are used to train and classify using Adaboost and HMM-based classifier. Experimental results show that temporal motion parameters perform much better than uniform motion parameters, and can be used to efficiently recognize facial expression.

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