Manifold based Sparse Representation for robust expression recognition without neutral subtraction
- 1 November 2011
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2136-2143
- https://doi.org/10.1109/iccvw.2011.6130512
Abstract
This paper exploits the discriminative power of manifold learning in conjunction with the parsimonious power of sparse signal representation to perform robust facial expression recognition. By utilizing an ℓ 1 reconstruction error and a statistical mixture model, both accuracy and tolerance to occlusion improve without the need to perform neutral frame subtraction. Initially facial features are mapped onto a low dimensional manifold using supervised Locality Preserving Projections. Then an ℓ 1 optimization is employed to relate surface projections to training exemplars, where reconstruction models on facial regions determine the expression class. Experimental procedures and results are done in accordance with the recently published extended Cohn-Kanade and GEMEP-FERA datasets. Results demonstrate that posed datasets overemphasize the mouth region, while spontaneous datasets rely more on the upper cheek and eye regions. Despite these differences, the proposed method overcomes previous limitations to using sparse methods for facial expression and produces state-of-the-art results on both types of datasets.Keywords
This publication has 20 references indexed in Scilit:
- Are sparse representations really relevant for image classification?Published by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- The first facial expression recognition and analysis challengePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Person-independent facial expression detection using Constrained Local ModelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Facial expression recognition on multiple manifoldsPattern Recognition, 2011
- Discriminant sparse nonnegative matrix factorizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Robust Face Recognition via Sparse RepresentationIeee Transactions On Pattern Analysis and Machine Intelligence, 2008
- FaceTracer: A Search Engine for Large Collections of Images with FacesLecture Notes in Computer Science, 2008
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency informationIEEE Transactions on Information Theory, 2006
- Stable recovery of sparse overcomplete representations in the presence of noiseIEEE Transactions on Information Theory, 2005
- Comprehensive database for facial expression analysisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002