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5th AVEC@ACM Multimedia 2015: Brisbane, Australia
- Fabien Ringeval, Björn W. Schuller, Michel F. Valstar, Roddy Cowie, Maja Pantic:
Proceedings of the 5th International Workshop on Audio/Visual Emotion Challenge, AVEC 2015, Brisbane, Australia, October 26, 2015. ACM 2015, ISBN 978-1-4503-3743-4
Keynote
- Roland Göcke:
AVEC 2015 Keynote Talk: From Facial Expression Analysis to Multimodal Mood Analysis. 1
Introduction
- Fabien Ringeval, Björn W. Schuller, Michel F. Valstar, Shashank Jaiswal, Erik Marchi, Denis Lalanne, Roddy Cowie, Maja Pantic:
AV+EC 2015: The First Affect Recognition Challenge Bridging Across Audio, Video, and Physiological Data. 3-8
AV+EC 2015 Part 1
- Markus Kächele, Patrick Thiam, Günther Palm, Friedhelm Schwenker, Martin Schels:
Ensemble Methods for Continuous Affect Recognition: Multi-modality, Temporality, and Challenges. 9-16 - Patrick Cardinal, Najim Dehak, Alessandro Lameiras Koerich, Jahangir Alam, Patrice Boucher:
ETS System for AV+EC 2015 Challenge. 17-23 - Yu Gu, Eric O. Postma, Hai-Xiang Lin:
Vocal Emotion Recognition with Log-Gabor Filters. 25-31 - Aleksandar Milchevski, Alessandro Rozza, Dimitar Taskovski:
Multimodal Affective Analysis combining Regularized Linear Regression and Boosted Regression Trees. 33-39
AV+EC 2015 Part 2
- Zhaocheng Huang, Ting Dang, Nicholas Cummins, Brian Stasak, Phu Ngoc Le, Vidhyasaharan Sethu, Julien Epps:
An Investigation of Annotation Delay Compensation and Output-Associative Fusion for Multimodal Continuous Emotion Prediction. 41-48 - Shizhe Chen, Qin Jin:
Multi-modal Dimensional Emotion Recognition using Recurrent Neural Networks. 49-56 - Hesam Sagha, Eduardo Coutinho, Björn W. Schuller:
Exploring the Importance of Individual Differences to the Automatic Estimation of Emotions Induced by Music. 57-63 - Linlin Chao, Jianhua Tao, Minghao Yang, Ya Li, Zhengqi Wen:
Long Short Term Memory Recurrent Neural Network based Multimodal Dimensional Emotion Recognition. 65-72 - Lang He, Dongmei Jiang, Le Yang, Ercheng Pei, Peng Wu, Hichem Sahli:
Multimodal Affective Dimension Prediction Using Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks. 73-80
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