Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes - Université de Bourgogne Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes

Résumé

Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage of these methods is that they have significantly lower computational requirements, as the extracted features are of very low dimensionality. This is achieved by modifying the previously proposed algorithm which considers Three-Orthogonal-Planes, to only Pairwise-Orthogonal-Planes. Performance of the algorithms was tested on the benchmark dataset provided by the Audio/Visual Emotion Challenge 2014, with the person-specific system achieving 97.6% classification accuracy, and the person-independed one yielding promising preliminary results of 74.5% accuracy. The paper concludes with open issues, proposed solutions, and future plans.
Fichier principal
Vignette du fichier
EMBC'16_0193_FINAL_MS.pdf (477.2 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01354878 , version 1 (19-08-2016)

Identifiants

  • HAL Id : hal-01354878 , version 1

Citer

Anastasia Pampouchidou, Kostas Marias, Manolis Tsiknakis, Panagiotis Simos, Fan Yang, et al.. Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes. 38th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Aug 2016, Orlando, United States. ⟨hal-01354878⟩
334 Consultations
344 Téléchargements

Partager

Gmail Facebook X LinkedIn More