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Emmanuel Dellandréa
Researcher at École centrale de Lyon
Publications - 106
Citations - 2332
Emmanuel Dellandréa is an academic researcher from École centrale de Lyon. The author has contributed to research in topics: Object detection & Audio signal. The author has an hindex of 25, co-authored 103 publications receiving 1864 citations. Previous affiliations of Emmanuel Dellandréa include University of Lyon & François Rabelais University.
Papers
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Journal ArticleDOI
Multi-stage classification of emotional speech motivated by a dimensional emotion model
TL;DR: Some new harmonic and Zipf based features for better speech emotion characterization in the valence dimension and a multi-stage classification scheme driven by a dimensional emotion model for better emotional class discrimination are proposed.
Proceedings ArticleDOI
Automatic Hierarchical Classification of Emotional Speech
TL;DR: A novel feature selection scheme based on the evidence theory is proposed for constructing a hierarchical classifier, which allows better performance than a global classifier as it is mostly used in the literature.
Book ChapterDOI
Image Categorization Using ESFS: A New Embedded Feature Selection Method Based on SFS
TL;DR: This paper introduces a novel embedded feature selection method, called ESFS, which is inspired from the wrapper method SFS since it relies on the simple principle to add incrementally most relevant features, leading to a lower computational cost than original SFS.
Proceedings Article
Overview of the ImageCLEF 2016 Scalable Concept Image Annotation Task
Andrew Gilbert,Luca Piras,Josiah Wang,Fei Yan,Arnau Ramisa,Emmanuel Dellandréa,Robert Gaizauskas,Mauricio Villegas,Krystian Mikolajczyk +8 more
TL;DR: Since 2010, ImageCLEF has run a scalable image annotation task, to promote research into the annotation of images using noisy web page data to improve image annotation, and there are interesting insights into these very relevant challenges.
Journal ArticleDOI
A unified probabilistic framework for automatic 3D facial expression analysis based on a Bayesian belief inference and statistical feature models
TL;DR: A unified probabilistic framework based on a novel Bayesian Belief Network (BBN) for 3D facial expression and Action Unit (AU) recognition and its robustness in landmark localization errors is presented.