Abstract
Towards realizing a multimodal affect recognition system, we are considering the advantages of assisting a visual-facial expression recognition system with keyboard-stroke pattern information. Our work is based on the assumption that the visual-facial and keyboard modalities are complementary to each other and that their combination can significantly improve the accuracy in affective user models. Specifically, we present and discuss the development and evaluation process of two corresponding affect recognition subsystems, with emphasis on the recognition of 6 basic emotional states, namely happiness, sadness, surprise, anger and disgust as well as the emotion-less state which we refer to as neutral. We find that emotion recognition by the visual-facial modality can be aided greatly by keyboard-stroke pattern information and the combination of the two modalities can lead to better results towards building a multimodal affect recognition system.
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References
Alepis, E., Virvou, M., Kabassi, K.: Affective student modeling based on microphone and keyboard user actions. In: ICALT ’06: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies, pp. 139–141. IEEE Computer Society,Washington, DC, USA (2006)
Berthouze, B.N., Kleinsmith, A.: A categorical approach to affective gesture recognition. Connection Science 15(4), 259–269 (2003). http://eprints.ucl.ac.uk/3368/
Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C.M., Kazemzadeh, A., Lee, S., Neumann, U., Narayanan, S.: Analysis of emotion recognition using facial expressions, speech and multimodal information. In: ICMI ’04: Proceedings of the 6th international conference on Multimodal interfaces, pp. 205–211. ACM, New York, NY, USA (2004). http://doi.acm.org/10.1145/1027933.1027968
Camurri, A., Lagerlöf, I., Volpe, G.: Recognizing emotion from dance movement: comparison of spectator recognition and automated techniques. Int. J. Hum.-Comput. Stud. 59(1-2), 213–225 (2003). http://dx.doi.org/10.1016/S1071-5819(03)00050-8
Chen, L.S., Huang, T.S., Miyasato, T., Nakatsu, R.: Multimodal human emotion/expression recognition. In: Proc. Int’l Conf. Automatic Face and Gesture Recognition, pp. 366–371 (1998)
Cowie, R., Douglas-cowie, E.: Automatic statistical analysis of the signal and prosodic signs of emotion in speech (1989)
Damasio, A.R.: Emotion in the perspective of an integrated nervous system. Brain Research Reviews 26, 83–86 (1998)
Damasio, A.R.: Fundamental feelings. Nature 413, 781 (2001)
Davidson, R., Pizzagalli, D., Nitschke, J., Kalin, N.: Handbook of Affective Sciences, chap. Parsing the subcomponents of emotion and disorders of emotion: perspectives from affective neuroscience. Oxford University Press, USA (2003)
Davidson, R., Scherer, K., Goldsmith, H.: andbook of Affective Sciences. Oxford, USA (2003)
De Silva, L., Miyasato, T., Nakatsu, R.: Facial Emotion Recognition Using Multimodal Information. In: Proceedings of IEEE Int. Conf. on Information, Communications and Signal Processing - ICICS. Singapore, Thailand (1997)
Goleman, D.: Emotional Intelligence. Bantam Books, New York, USA
Graf, H., Cosatto, E., Strom, V., Huang, F.: Visual prosody: Facial movements accompanying speech. In: 5th IEEE International Conference on Automatic Face and Gesture Recognition, pp. 381–386 (2002)
Gunes, H., Piccardi, M.: A bimodal face and body gesture database for automatic analysis of human nonverbal affective behavior. In: ICPR ’06: Proceedings of the 18th International Conference on Pattern Recognition, pp. 1148–1153. IEEE Computer Society, Washington, DC, USA (2006). http://dx.doi.org/10.1109/ICPR.2006.39
Isbister, K., Hook, K.: Evaluating affective interactions (introduction to special issue). International journal of human-computer studies 65(4), 273–274 (2007)
Kaliouby, R., Robinson, P.: Generalization of a vision-based computational model of mindreading. pp. 582–589 (2005). 10.1007/11573548 75. http://dx.doi.org/10.1007/11573548 75
Liao, W., Zhang, W., Zhu, Z., Ji, Q., Gray, W.D.: Toward a decision-theoretic framework for affect recognition and user assistance. Int. J. Hum.-Comput. Stud. 64(9), 847–873 (2006). http://dx.doi.org/10.1016/j.ijhcs.2006.04.001
Oviatt, S.: User-centered modeling and evaluation of multimodal interfaces. IEEE Proceedings 91(B), 1457–1468 (2003)
Pantic, M., Rothkrantz, L.J.M.: Automatic analysis of facial expressions: the state of the art. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1424–1445 (2000)
Pantic, M., Rothkrantz, L.J.M.: Toward an affect-sensitive multimodal human-computer interaction. In: Proceedings of the IEEE, pp. 1370–1390 (2003)
Pantic, M., Rothkrantz, L.J.M.: Toward an affect-sensitive multimodal human-computer interaction. Proceedings of the IEEE 91(9), 1370–1390 (2003). 10.1109/JPROC.2003.817122
Picard, R.: Affective computing: challenges. Internationa Journal of Human-Computer Studies 59(1-2), 55–64 (2003). 10.1016/S1071-5819(03)00052-1
Picard, R.W., Vyzas, E., Healey, J.: Toward machine emotional intelligence: Analysis of affective physiological state. IEEE Transactions on Pattern Analysis and Machine Intelligence 23, 1175–1191 (2001)
Pierrakos, D., Papatheodorou, G.P.C., Spyropoulos, C.: Web usage mining as a tool for personalization: A survey. User Modeling and User Adapted Interaction 13(4), 311–372 (2003)
Scherer, K.R.: Adding the affective dimension: A new look in speech analysis and synthesis. pp. 1808–1811 (1996)
Stathopoulou, I.O., Tsihrintzis, G.: A neural network-based facial analysis system. In: Proceedings of the 5th International Workshop on Image Analysis for Multimedia Interactive Services. Lisboa, Portugal (2004)
Stathopoulou, I.O., Tsihrintzis, G.: An Improved Neural Network-Based Face Detection and Facial Expression Classification System. In: IEEE International Conference on Systems, Man, and Cybernetics. The Hague, Netherlands (2004)
Stathopoulou, I.O., Tsihrintzis, G.: Detection and Expression Classification Systems for Face Images (FADECS). In: Proceedings of the IEEE Workshop on Signal Processing Systems (SiPS05). Athens, Greece (2005)
Stathopoulou, I.O., Tsihrintzis, G.: Evaluation of the Discrimination Power of Features Extracted from 2-D and 3-D Facial Images for Facial Expression Analysis. In: Proceedings of the 13th European Signal Processing Conference. Antalya, Turkey (2005)
Stathopoulou, I.O., Tsihrintzis, G.: Pre-processing and expression classification in low quality face images. In: Proceedings of 5th EURASIP Conference on Speech and Image Processing, Multimedia Communications and Services (2005)
Stathopoulou, I.O., Tsihrintzis, G.: An Accurate Method for eye detection and feature extraction in face color images. In: Proceedings of the 13th International Conference on Signals, Systems, and Image Processing. Budapest, Hungary (2006)
Stathopoulou, I.O., Tsihrintzis, G.: Facial Expression Classification: Specifying Requirements for an Automated System. In: Proceedings of the 10th International Conference on Knowledge-Based Intelligent Information Engineering Systems, LNAI: Vol. 4252, pp. 1128–1135. Springer-Verlag, Berlin, Heidelberg (2006). http://dx.doi.org/10.1007/11893004
Stathopoulou, I.O., Tsihrintzis, G.A.: Neu-faces: A neural network-based face image analysis system. In: ICANNGA ’07: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II, LNCS: Vol. 4432, pp. 449–456. Springer-Verlag, Berlin, Heidelberg (2007). http://dx.doi.org/10.1007/978-3-540-71629-751
Stathopoulou, I.O., Tsihrintzis, G.A.: Comparative performance evaluation of artificial neural network-based vs. human facial expression classifiers for facial expression recognition. In: KES-IMSS 2008: 1st International Symposium on Intelligent Interactive Multimedia Systems and Services, SCI: Vol. 142, pp. 55–65. Springer-Verlag, Berlin, Heidelberg (2008). http://dx.doi.org/10.1007/978-3-540-68127-4
Virvou, M., Tsihrintzis, G.A., Alepis, E., Stathopoulou, I.O., Kabassi, K.: Combining empirical studies of audio-lingual and visual-facial modalities for emotion recognition. In: KES ’07: Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference, LNAI: Vol. 4693, pp. 1130–1137. Springer-Verlag, Berlin, Heidelberg (2007). http://dx.doi.org/10.1007/978-3-540-74827-4141
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Stathopoulou, IO., Alepis, E., Tsihrintzis, G., Virvou, M. (2010). On Assisting a Visual-Facial Affect Recognition System with Keyboard-Stroke Pattern Information. In: Bramer, M., Ellis, R., Petridis, M. (eds) Research and Development in Intelligent Systems XXVI. Springer, London. https://doi.org/10.1007/978-1-84882-983-1_35
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DOI: https://doi.org/10.1007/978-1-84882-983-1_35
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