Affective computing

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Affective computing

  1. 1. Ankit Kumar MoonkaAnkit Kumar Moonka Sonam Rani MishraSonam Rani Mishra B.Tech 6B.Tech 6thth SemesterSemester Affective Computing or Better Intelligence Systems
  2. 2.  What’s Affective Computing ? ?  Why go For Affective Computing ? ?  Motivation & Goals  Applications  Affective Computing research  Detection & Recognition  Concerned issues  Future Developments  Conclusion Main topics
  3. 3. Introduction to Affective Computing
  4. 4. Producing emotional response According to Picard – “…computing that relates to, arises from, or deliberately influences emotions” Affective Computing – ability for the computer to recognize and express emotions as humans do But do not have emotion. WHAT IS AFFECTIVE COMPUTING?
  5. 5. Humans naturally communicate affectively; expression identified 50% of the time. Human-Computer Interaction – Frustration, mouse clicking behavior, slow, debugging, so we need friendlier HCI.
  6. 6. Affective Computing Motivations and Goals  Research shows that human intelligence is not independent of emotion. Emotion and cognitive functions are inextricably integrated into the human brain.  Automatic assessment of human emotional/affective state.  Creating a bridge between highly emotional human and emotionally challenged computer systems/electronic devices - Systems capable of responding emotionally.  The central issues in affective computing are representation, detection, and classification of users emotions.
  7. 7. ApplicationsApplications Hands-free computing Social interfacesSocial interfaces Distance education Internet banking
  8. 8. Applications (Contd.)Applications (Contd.)  Security sectorSecurity sector  Medical sectorMedical sector  NeurologyNeurology  PsychiatryPsychiatry  Dialog/Automatic call center Environment – to reduceDialog/Automatic call center Environment – to reduce user/customer frustrationuser/customer frustration Zhihong Zeng; Pantic, M.; Roisman, G.I.; Huang, T.S.; , "A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions," Pattern Analysis and Machine Intelligence
  9. 9. ∗ Affective computing can be related to other computing disciplines such as Artificial Intelligence (AI), Virtual Reality (VR) and Human Computer interaction (HCI). ∗ Questions need to be answered: What we mean when we use the word emotion? What is an affective state (typically feelings, moods, etc.)? Which human communicative signals convey information about affective state? How to apply affective information to designing systems? AFFECTIVE COMPUTING RESEARCH
  10. 10. Steps towards affective computing research  We first need to define what we mean when we use the word emotion.  Second, we need an emotion model that gives us the possibility to differentiate between emotional states.  In addition, we need a classification scheme that uses specific features from an underlying (input) signal to recognize the user’s emotions .  The emotion model has to fit together with the classification scheme used by the emotion recognizer. R. Sharma, V. Pavlovic, and T. Huang. Toward multimodal human-computer interface. In Proceedings of the IEEE, 1998.
  11. 11. Affection detection sources: ∗ Bio-signals (Psychological sensors, Wearable sensors) ∗ Brain Signal, skin temperature, blood pressure, heart rate, respiration rate ∗ Facial & Speech/Vocal Expression ∗ Gesture & Text ∗ Limbic movements AFFECTION DETECTION AND RECOGNITION
  12. 12. Affection Recognition Method Speech Recognition Architecture Feature ExtractionPre-processing Speech Signal Classification Classified Result Audio recordings collected in call centers and, meetings, Wizard of Oz scenarios interviews and other dialogue systems • Accuracy rates from speech are somewhat lower (35%) than facial expressions for the basic emotions . • Sadness, anger, and fear are the emotions that are best recognized through voice, while disgust is the worst. ]M. Pantic, N. Sebe, J. F. Cohn, and T. Huang. Affective multimodal human-computer interaction. In ACM International Conference on Multimedia (MM), 2005. Rafael A. Calvo, Sidney D'Mello, "Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications
  13. 13. Concerned Issues ∗ Privacy concerns ∗ I do not want the outside world to know what goes through my mind…Twitter is the limit ∗ Risk of misuse of the technology ∗ In the hand of impostors ∗ Computers start to make emotionally distorted, harmful decisions ∗ Complex technology ∗ Effectiveness is still questionable, risk of false interpretation
  14. 14. FUTURE RESEARCH DIRECTIONS ∗So far Context has been overlooked in most Affection Computing researches ∗Collaboration among Affection researchers from different disciplines ∗Fast real-time processing ∗Multimodal detection and recognition to achieve higher accuracy ∗Systems that can model conscious and subconscious user behavior
  15. 15. Context Aware Multimodal Affection Analysis Based Smart Learning Environment 17
  16. 16. Conclusion 18 “Ultimately, affective- computing technology could eliminate the need for devices that today stymie and frustrate users… Affective computing is an important development in computing, because as pervasive or ubiquitous computing becomes mainstream, computers will be far more invisible and natural in their interactions with humans.” Toyota’s thought controlled wheelchair
  17. 17. 19
  18. 18. 20 QUERIES???
  19. 19. References [1] Picard, R. 1995. Affective Computing. M.I.T Media Laboratory Perceptual Computing Section Technical Report No. 321 [2] Picard, R. 1995. Affective Computing. The MIT Press. ISBN-10: 0-262-66115-2. [3] Picard, R., & Klein, J. (2002). Computers that recognize and respond to user emotion: Theoretical and practical implications. Interacting With Computers, 14, 141-169. [4] http://www.sric-bi.com/ [5] Bullington, J. 2005. ‘Affective’ computing and emotion recognition systems: The future of biometric surveillance? Information Security Curriculum Development (InfoSecCD) Conference '05, September 23-24, 2005, Kennesaw, GA, USA. [6] Boehner, K., DePaula, R., Dourish, P. & Sengers, P. 2005. Affect: From Information to Interaction. AARHUS’05 8/21-8/25/05 Århus, Denmark. [7] Zeng, Z. et al. 2004. Bimodal HCI-related Affect Recognition. ICMI’04, October 13–15, 2004, State College, Pennsylvania, USA. [8] Taleb, T.; Bottazzi, D.; Nasser, N.; , "A Novel Middleware Solution to Improve Ubiquitous Healthcare Systems Aided by Affective Information," Information Technology in Biomedicine, IEEE Transactions on , vol.14, no.2, pp.335-349, March 2010 [9] Khosrowabadi, R. et al. 2010. EEG-based emotion recognition using self-organizing map for boundary detection. International Conference on Pattern Recognition, 2010. [10] R. Cowie, E. Douglas, N. Tsapatsoulis, G. Vostis, S. Kollias, w. Fellenz and J. G. Taylor, Emotion Recognition in Human-computer Interaction. In: IEEE Signal Processing Magazine, Band 18 p.32 - 80, 2001. [11] Rafael A. Calvo, Sidney D'Mello, "Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications," IEEE Transactions on Affective Computing, pp. 18-37, January-June, 2010 [12] Zhihong Zeng; Pantic, M.; Roisman, G.I.; Huang, T.S.; , "A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.31, no.1, pp.39-58, Jan. 2009 [13] Norman, D.A. (1981). ‘Twelve issues for cognitive science’, Perspectives on Cognitive Science, Hillsdale, NJ: Erlbaum, pp.265–295. [14] R. Sharma, V. Pavlovic, and T. Huang. Toward multimodal human-computer interface. In Proceedings of the IEEE, 1998. [15] Vesterinen, E. (2001). Affective Computing. Digital media research seminar, spring 2001: “Space Odyssey 2001”.
  20. 20. References [16] Burkhardt, F.; van Ballegooy, M.; Engelbrecht, K.-P.; Polzehl, T.; Stegmann, J.; , "Emotion detection in dialog systems: Applications, strategies and challenges," Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on , vol., no., pp.1-6, 10-12 Sept. 2009 [17] Leon, E.; Clarke, G.; Sepulveda, F.; Callaghan, V.; , "Optimised attribute selection for emotion classification using physiological signals," Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE , vol.1, no., pp.184-187, 1-5 Sept. 2004 [19] http://www.engadget.com/2009/06/30/toyotas-mind-controlled-wheelchair-boast-fastest-brainwave-anal/ [20] http://www.w3.org/TR/2009/WD-emotionml-20091029/ [21] M. Pantic, N. Sebe, J. F. Cohn, and T. Huang. Affective multimodal human-computer interaction. In ACM International Conference on Multimedia (MM), 2005. [22] Gong, L., Wang, T., Wang, C., Liu, F., Zhang, F., and Yu, X. 2010. Recognizing affect from non-stylized body motion using shape of Gaussian descriptors. In Proceedings of the 2010 ACM Symposium on Applied Computing (Sierre, Switzerland, March 22 - 26, 2010). SAC '10. ACM, New York, NY, 1203-1206. [23] Khalili, Z.; Moradi, M.H.; , "Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG," Neural Networks, 2009. IJCNN 2009. International Joint Conference on , vol., no., pp.1571-1575, 14-19 June 2009 [24] Huaming Li and Jindong Tan. 2007. Heartbeat driven medium access control for body sensor networks. In Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments (HealthNet '07). ACM, New York, NY, USA, 25-30. [25] Ghandi, B.M.; Nagarajan, R.; Desa, H.; , "Facial emotion detection using GPSO and Lucas-Kanade algorithms," Computer and Communication Engineering (ICCCE), 2010 International Conference on , vol., no., pp.1-6, 11-12 May 2010 [26] Lucey, P.; Cohn, J.F.; Kanade, T.; Saragih, J.; Ambadar, Z.; Matthews, I.; , "The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression," Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on , vol., no., pp.94-101, 13-18 June 2010 [27] Ruihu Wang; Bin Fang; , "Affective Computing and Biometrics Based HCI Surveillance System," Information Science and Engineering, 2008. ISISE '08. International Symposium on , vol.1, no., pp.192-195, 20-22 Dec. 2008

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