Head-Pose Invariant Facial Expression Recognition Using Convolutional Neural Networks

Automatic face analysis has to cope with pose and lighting variations. Especially pose variations are difficult to tackle and many face analysis methods require the use of sophisticated normalization and initialization procedures. We propose a data-driven face analysis approach that is not only capa...

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Bibliographic Details
Published in:	Multimodal Interfaces: Proceedings of the International Conference on Multimodal Interfaces (4th: 2002: Pittsburgh, PA) p. 529
Main Author:	Fasel, Beat
Format:	Conference Proceeding
Language:	English
Published:	Washington, DC, USA IEEE Computer Society 14.10.2002 IEEE
Series:	ACM Conferences
Subjects:	Automatic testing Character recognition Computing methodologies Computing methodologies > Artificial intelligence Computing methodologies > Artificial intelligence > Computer vision Computing methodologies > Artificial intelligence > Computer vision > Computer vision problems Computing methodologies > Artificial intelligence > Computer vision > Computer vision problems > Object recognition Computing methodologies > Machine learning Computing methodologies > Machine learning > Machine learning approaches Computing methodologies > Machine learning > Machine learning approaches > Neural networks Convolution Data analysis Face recognition Feature extraction Neural networks Neurons Performance analysis Robustness
ISBN:	9780769518343, 0769518346
Online Access:	Get full text
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