In this article we address the issue of adopting a local sparse coding representation (Histogram of Sparse Codes), in a part-based framework for inferring the locations of facial landmarks. The rationale behind this approach is that unsupervised learning of sparse code dictionaries from face data can be an effective approach to cope with such a challenging problem. Results obtained on the CMU Multi-PIE Face dataset are presented providing support for this approach.
Using sparse coding for landmark localization in facial expressions / V. Cuculo, R. Lanzarotti, G. Boccignone - In: 5. European workshop on visual information processing (EUVIP 2014) : December 10-12, 2014, Paris, France[Piscataway (New Jersey)] : IEEE, 2014 Dec. - ISBN 9781479945726. - pp. 1-6 (( Intervento presentato al 5. convegno European workshop on visual information processing (EUVIP) tenutosi a Parigi nel 2014 [10.1109/EUVIP.2014.7018369].
Using sparse coding for landmark localization in facial expressions
V. Cuculo;R. Lanzarotti;G. Boccignone
2014
Abstract
In this article we address the issue of adopting a local sparse coding representation (Histogram of Sparse Codes), in a part-based framework for inferring the locations of facial landmarks. The rationale behind this approach is that unsupervised learning of sparse code dictionaries from face data can be an effective approach to cope with such a challenging problem. Results obtained on the CMU Multi-PIE Face dataset are presented providing support for this approach.File | Dimensione | Formato | |
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