Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name :  Damodharam Seenu  | B Siva kesava reddy | L Balajiunnamed

Volume 03 Issue 05 2016

ISSN no:  2348-3121

Page no: 16-18

Abstract- This paper proposes an approach called Extreme Sparse Learning (ESL), which has the ability to jointly learn a dictionary (set of basis) and a non-linear classification model. The proposed approach combines the discriminative power of Extreme Learning Machine (ELM) with the reconstruction property of sparse representation to enable accurate classification when presented with noisy signals and imperfect data recorded in natural settings. Additionally, this work presents a new local spatio-temporal descriptor that is distinctive and pose-invariant. The proposed framework is able to achieve state-of-the-art recognition accuracy on both acted and spontaneous facial emotion databases.

KeywordsExtreme Sparse Learning, non-linear, spatio-temporal


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