AVEC 2014 - 3D dimensional affect and depression recognition challenge

AVEC 2014 - Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge, Workshop of MM 2014

Volumn , Issue , 2014, Pages 3-10

  Valstar, Michel ^a   Schuller, Björn ^b,e   Smith, Kirsty ^a   Almaev, Timur ^a   Eyben, Florian ^b   Krajewski, Jarek ^c   Cowie, Roddy ^d   Pantic, Maja ^e,f  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^c UNIVERSITY OF WUPPERTAL   (Germany)

^d QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

^e IMPERIAL COLLEGE LONDON   (United Kingdom)

^f UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Affective computing; Challenge; Emotion recognition; Facial expression; Speech

Indexed keywords

SPEECH; SURVEYS;

AFFECTIVE COMPUTING; BASELINE SYSTEMS; CHALLENGE; CONTINUOUS VALUE; EMOTION RECOGNITION; FACIAL EXPRESSIONS; MOOD DISORDERS; TEMPORAL CORRELATIONS;

SPEECH RECOGNITION;

EID: 84910596152     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2661806.2661807     Document Type: Conference Paper

References (32)

1. T. Almaev and M. Valstar. Local gabor binary patterns from three orthogonal planes for automatic facial expression recognition. In Proc. Affective Computing and Intelligent Interaction, 2013.
2. T. R. Almaev, A. Yüce, A. Ghitulescu, and M. F. Valstar. Distribution-based iterative pairwise classification of emotions in the wild using lgbp-top. In Proc. Int'l Conf. Multimodal Interaction, ICMI '13, pages 535-542, New York, NY, USA, 2013. ACM.
3. M. R. Bagby, A. G. Ryder, D. R. Schuller, and M. B. Marshall. The hamilton depression rating scale: Has the gold standard become a lead weight? American Journal of Psychiatry, 161:2163-2177, 2004.
4. A. Beck, R. Steer, R. Ball, and W. Ranieri. Comparison of beck depression inventories -ia and -ii in psychiatric outpatients. Journal of Personality Assessment, 67(3):588-97, December 1996.
5. J. F. Cohn, S. Kreuz, I. Matthews, Y. Yang, M. H. Nguyen, M. Tejera Padilla, and et al. Detecting depression from facial actions and vocal prosody. In Proc. Affective Computing and Intelligent Interaction, pages 1-7, 2009.
6. R. Cowie, E. Douglas-Cowie, S. Savvidou, E. McMahon, M. Sawey, and M. Schröder. Feeltrace: An instrument for recording perceived emotion in real time. In Proc. ISCA Workshop on Speech and Emotion, pages 19-24, Belfast, UK, 2000.
7. F. Eyben, F. Weninger, S. Squartini, and B. Schuller. Real-life voice activity detection with lstm recurrent neural networks and an application to hollywood movies. In Proc. of ICASSP, Vancouver, Canada. IEEE, 2013. to appear.
8. F. Eyben, M. Wöllmer, and B. Schuller. openEAR - Introducing the Munich Open-Source Emotion and Affect Recognition Toolkit. In Proc. ACII, pages 576-581, Amsterdam, The Netherlands, 2009.
9. F. Eyben, M. Wöllmer, and B. Schuller. openSMILE - The Munich Versatile and Fast Open-Source Audio Feature Extractor. In Proc. ACM Multimedia (MM), pages 1459-1462, Florence, Italy, 2010.
10. M. First, R. Spitzer, M. Gibbon, and J. Williams. Structured Clinical Interview for DSM-IV Axis I Disorders SCID-I: Clinician Version, Administration Booklet. SCID-I: Clinician Version. American Psychiatric Press, 1997.
11. J. Fontaine, S. K.R.E. Roesch, and P. Ellsworth. The world of emotions is not two-dimensional. Psychological science, 18(2):1050 - 1057, 2007.
12. J. M. Girard, J. F. Cohn, M. H. Mahoor, S. Mavadati, and D. Rosenwald. Social risk and depression: Evidence from manual and automatic facial expression analysis. In IEEE International Conference on Automatic Face and Gesture Recognition, 2013.
13. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten. The weka data mining software: An update. SIGKDD Explor. Newsl., 11(1):10-18, Nov. 2009.
14. M. Hamilton. Development of a rating scale for primary depressive illness. British Journal of Social and Clinical Psycology, 8:278-296, 1967.
15. J. Hamm, Kohler, C. G., Gur, R. C., and R. Verma. Automated facial action coding system for dynamic analysis of facial expressions in neuropsychiatric disorders. Journal of Neuroscience Methods, 200(2):237-256, 2011.
16. Health & Consumer Protection Directorate General. Improving the mental health of the population: Towards a strategy on mental health for the european union. Technical report, European Union, 2005.
17. Health & Consumer Protection Directorate General. Mental health in the eu. Technical report, European Union, 2008.
18. M. Kächele, M. Glodek, D. Zharkov, S. Meudt, and F. Schwenker. Fusion of audio-visual features using hierarchical classifier systems for the recognition of affective states and the state of depression. In M. De Marsico, A. Tabbone, and A. Fred, editors, Proc. Int'l Conf. Pattern Recognition Applications and Methods (ICPRAM), pages 671-678. SciTePress, 2014.
19. S. Maji, A. C. Berg, and J. Malik. Classification using intersection kernel support vector machines is efficient. 2013 IEEE Conference on Computer Vision and Pattern Recognition, 0:1-8, 2008.
20. H. Meng, D. Huang, H. Wang, H. Yang, M. AI-Shuraifi, and Y. Wang. Depression recognition based on dynamic facial and vocal expression features using partial least square regression. In Proc. Int'l Workshop Audio/Visual Emotion Challenge, AVEC '13, pages 21-30, New York, NY, USA, 2013. ACM.
21. M. Nicolaou, V. Pavlovic, and M. Pantic. Dynamic probabilistic cca for analysis of affective behaviour and fusion of continuous annotations. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PP(99):1-1, 2014.
22. R. Picard. Affective Computing. MIT Press, 1997.
23. S. Scherer, G. Stratou, J. Gratch, J. Boberg, M. Mahmoud, A. S. Rizzo, and L.-P. Morency. Automatic behavior descriptors for psychological disorder analysis. In Proc. IEEE Int. Conf. on Automatic Face and Gesture Recognition, 2013.
24. B. Schuller, S. Steidl, and A. Batliner. The INTERSPEECH 2009 Emotion Challenge. In Proc. INTERSPEECH 2009, pages 312-315, Brighton, UK, 2009.
25. B. Schuller, S. Steidl, A. Batliner, F. Burkhardt, L. Devillers, C. Müller, and S. Narayanan. The INTERSPEECH 2010 Paralinguistic Challenge. In Proc. INTERSPEECH 2010, pages 2794-2797, Makuhari, Japan, 2010.
26. M. Valstar. Automatic behaviour understanding in medicine. In Proceedings ACM Int'l Conf. Multimodal Interaction, 2014.
27. M. Valstar, B. Schuller, K. Smith, F. Eyben, B. Jiang, S. Bilakhia, S. Schnieder, R. Cowie, and M. Pantic. Avec 2013 - the continuous audio/visual emotion and depression recognition challenge. In Proc. 3rd ACM international workshop on Audio/visual emotion challenge, pages 3-10, 2013.
28. A. Vinciarelli, M. Pantic, D. Heylen, C. Pelachaud, I. Poggi, F. D'ericco, and M. Schroeder. Bridging the gap between social animal and unsocial machine: A survey of social signal processing. IEEE Trans. Affective Computing, 3:69-87, April 2012. Issue 1.
29. P.Wang, F. Barrett, E. Martin, M. Milonova, R. E. Gur, R. C. Gur, C. Kohler, et al. Automated video-based facial expression analysis of neuropsychiatric disorders. Journal of Neuroscience Methods, 168(1):224 - 238, 2008.
30. J. R. Williamson, T. F. Quatieri, B. S. Helfer, R. Horwitz, B. Yu, and D. D. Mehta. Vocal biomarkers of depression based on motor incoordination. In Proceedings of the 3rd ACM International Workshop on Audio/Visual Emotion Challenge, AVEC '13, pages 41-48, New York, NY, USA, 2013. ACM.
31. Y. Yang, C. Fairbairn, and J. Cohn. Detecting depression severity from intra- and interpersonal vocal prosody. IEEE Transactions on Affective Computing, 4, 2013.
32. M. Zimmerman, I. Chelminski, and M. Posternak. A review of studies of the hamilton depression rating scale in healthy controls: Implications for the definition of remission in treatment studies of depression. Journal of Nervous & Mental Disease, 192(9):595-601, 2004.