Robust EEG emotion classification using segment level decision fusion

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2013, Pages 1286-1290

  Rozgic, Viktor ^a   Vitaladevuni, Shiv N ^a   Prasad, Rohit ^a  

^a BBN TECHNOLOGIES   (United States)

Author keywords

EEG; emotion recognition

Indexed keywords

AUDIO-VISUAL STIMULUS; BINARY CLASSIFICATION; CLASSIFICATION ACCURACY; ELECTROENCEPHALOGRAM SIGNALS; EMOTION CLASSIFICATION; EMOTION RECOGNITION; EMOTIONAL DIMENSIONS; NEAREST NEIGHBOR MODEL;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; SIGNAL PROCESSING;

ELECTROENCEPHALOGRAPHY;

EID: 84890534659     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2013.6637858     Document Type: Conference Paper

References (19)

1. B. Schuller, A. Batliner, S. Steidl, and D. Seppi. "Recognising Realistic Emotions and Affect in Speech: State of the Art and Lessons Learnt from the First Challenge." Speech Communication, 53(10), 2011.
2. C. O. Alm, D. Roth, and R. Sproat. "Emotions from text: machine learning for text-based emotion prediction." In Proc. Human Language Technology and Empirical Methods in Natural Language Processing, (HLT/EMLP) 2005.
3. Busso, Carlos, et al. "Analysis of emotion recognition using facial expressions, speech and multimodal information." In Proc. International Conference on Multimodal Interfaces (ICMI), 2004.
4. F. Nasoz et al. "Emotion recognition from physiological signals using wireless sensors for presence technologies." Cognition, Technology & Work 6.1 (2004): 4-14.
5. S. Koelstra, C. Muehl, M. Soleymani, J.-S. Lee, A. Yazdani, T. Ebrahimi, T. Pun, A. Nijholt, and I. Patras. "DEAP: A Database for Emotion Analysis using Physiological Signals, In IEEE Trans. on Affective Computing, Special Issue on Naturalistic Affect Resources for System Building and Evaluation, in press
6. S. Koelstra, A. Yazdani, M. Soleymani, C. Muehl, J.-S. Lee, A. Nijholt, T. Pun, T. Ebrahimi, and I. Patras. "Single Trial Classification of EEG and Peripheral Physiological Signals for Recognition of Emotions Induced by Music Videos." In Proc. Conference on Brain Informatics, 2010.
7. P. C. Petrantonakis and L. J. Hadjileontiadis. "Emotion Recognition from Brain Signals Using Hybrid Adaptive Filtering and Higher-Order Crossings Analysis." IEEE Trans. on Affective Computing, accepted for publication.
8. R. Khosrowabadi, C. Q. Hiok, A. Wahab, and K. A. Kai. "EEG-based Emotion Recognition Using Self-Organizing Map for Boundary Detection." In Proc. Pattern Recognition (ICPR), 2010
9. Y. Liu, O. Sourina, and M. K. Nguyen. "Real-Time EEG-based Emotion Recognition and Applications." In Trans. on Computational Science, 256-278, 2011
10. K. Takahashi. "Remarks on SVM-based emotion recognition from multi-modal bio-potential signals," In Proc. Robot and Human Interactive Communication (ROMAN) 2004.
11. Y-P. Lin, C-H. Wang, T-P. Jung, T-L. Wu, S-K. Jeng, J-R. Duann and J-H. Chen."EEG-Based Emotion Recognition in Music Listening." In Trans IEEE on Biomedical Engineering, 57(7), 2010
12. D. Nie, X-W. Wang, L-C. Shi, and B-L. Lu. "EEG-based Emotion Recognition during Watching Movies." In Proc EMBS Conference on Neural Engineering, 2011
13. O. Boiman, E. Shechtman, and M. Irani. "In defense of nearest-neighbor based image classification." Computer Vision and Pattern Recognition, 2008. CVPR 2008
14. T. Tuytelaars, M. Fritz, K. Saenko, T. Darrell. "The NBNN kernel." In Proc. International Conference on Computer Vision (ICCV), 2011
15. S. Lafon. "Diffusion Maps and Geometric Harmonics." Ph.D. thesis, Yale University, 2004.
16. T. P. Minka. "Estimating a Dirichlet distribution." Tech. Report, Microsoft Reasearch, 2000
17. N. Wicker, J. Muller, K. R. Kalathur, O. Poch. "A maximum likelihood approximation method for Dirichlet's parameter estimation." Journal of Comput. Stat. and Data Anal., 52(3), 2008
18. V. Vapnik. "The Nature of Statistical Learning Theory." Springer-Verlag, New York, 1995.
19. B. Schölkopf, A. Smola, and K-R. Müller. "Kernel principal component analysis." Artificial Neural Networks, ICANN'97