Skip to main content
SpringerLink
Log in

Affect in Multimodal Information

  • Chapter
Affective Information Processing

Abstract

In face-to-face communication, the emotional state of the speaker is transmitted to the listener through a synthetic process that involves both the verbal and thenonverbal modalities of communication. From this point of view, the transmission of the information content is redundant, because the same information is transferred through several channels as well. How much information about the speaker's emotional state is transmitted by each channel and which channel plays the major role in transferring such information? The present study tries to answer these questions through a perceptual experiment that evaluates the subjective perception of emotional states through the single (either visual or auditory channel) and the combined channels (visual and auditory). Results seem to show that, taken separately, the semantic content of the message and the visual content of the message carry the same amount of information as the combined channels, suggesting that each channel performs a robust encoding of the emotional features that is very helpful in recovering the perception of the emotional state when one of the channels is degraded by noise.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Ali, S. M.,&Silvey, S. D. (1996). A general class of coefficients of divergence of one distribution from another.Journal of Royal Statistic Society,28,131–142.

    MathSciNet  Google Scholar 

  • Apolloni, B., Aversano, G.,&Esposito, A. (2000). Preprocessing and classification of emotional features in speech sentences. In Y. Kosarev (Ed.),Proceedings. IEEE Workshop on Speech and Computer(pp. 49–52).

    Google Scholar 

  • Apolloni, B., Esposito, A., Malchiodi, D., Orovas, C., Palmas, G.,&Taylor, J. G. (2004). A general framework for learning rules from data.IEEE Transactions on Neural Networks, 15(6), 1333– 1350.

    Article  Google Scholar 

  • Apple, W.,&Hecht, K. (1982). Speaking emotionally: The relation between verbal and vocal communication of affect.Journal of Personality and Social Psychology,42, 864–875.

    Article  Google Scholar 

  • Argyle, M. (1988).Bodily communication. New York: Methuen.

    Google Scholar 

  • Bachorowski, J. A. (1999). Vocal expression and perception of emotion.Current Directions in Psychological Science,8, 53–57.

    Article  Google Scholar 

  • Banse, R.,&Scherer, K. (1996). Acoustic profiles in vocal emotion expression.Journal of Personality&Social Psychology 70(3), 614–636.

    Article  Google Scholar 

  • Bartneck, C. (2000).Affective expressions of machines. Eindhoven: Stan Ackerman Institute.

    Google Scholar 

  • Beattie G. W. (1981). Language and non-verbal communication: The essential synthesis.Linguistics,19, 1165–1183.

    Article  Google Scholar 

  • Bermond, B., Nieuwenhuyse, B., Fasotti, L.,&Schuerman, J. (1991). Spinal cord lesions, peripheral feedback, and intensities of emotional feelings.Cognition and Emotion 5, 201–220.

    Article  Google Scholar 

  • Bourbakis, N. G., Esposito, A.,&Kavraki, D. (2006). Analysis of invariant meta-features for learning and understanding disable people's emotional behavior related to their health conditions: A case study. InProceedings of Sixth International IEEE Symposium BioInformatics and BioEngineering, IEEE Computer Society (pp. 357–369).

    Google Scholar 

  • Bourbakis, N. G., Esposito, A.,&Kavraki, D. (2007). Multi-modal interfaces for interaction-communication between hearing and visually impaired individuals: Problems&issues. InProceedings of the International Conference on Tool for Artificial Intelligence, Patras, Greece, Oct. 29–31 (pp. 1–10).

    Google Scholar 

  • Bradley, M. M., Cuthbert, B. N.,&Lang, P. J. (1990). Startle reflex modification: Emotion or attention?Psychophysiology,27, 513–523.

    Article  Google Scholar 

  • Breitenstein, C., Van Lancker, D.,&Daum, I. (2001). The contribution of speech rate and pitch variation to the perception of vocal emotions in a German and an American sample.Cognition&Emotion,15(1), 57–79.

    Google Scholar 

  • Bryll, R., Quek, F.,&Esposito, A. (2001). Automatic hand hold detection in natural conversation. InProceedings of IEEE Workshop on Cues in Communication, Hawai, December 9.

    Google Scholar 

  • Burns, K. L.,&Beier, E. G. (1973). Significance of vocal and visual channels in the decoding of emotional meaning.Journal of Communication,23, 118–130.

    Article  Google Scholar 

  • Butterworth, B. L.,&Beattie, G. W. (1978). Gestures and silence as indicator of planning in speech. In R. N. Campbell&P. T. Smith (Eds.),Recent Advances in the Psychology of Language(pp. 347–360). New York: Olenum Press.

    Google Scholar 

  • Butterworth, B. L.,&Hadar, U. (1989). Gesture, speech, and computational stages: a reply to McNeill.Psychological Review,96, 168–174.

    Article  Google Scholar 

  • Caccioppo, J. T., Bush, L. K.,&Tassinary, L. G. (1992). Microexpressive facial actions as functions of affective stimuli: Replication and extension.Personality and Social Psychology Bulletin,18, 515–526.

    Article  Google Scholar 

  • Caccioppo, J. T., Klein, D. J., Bernston, G. C.,&Hatfield, E. (1993). The psychophysiology of emotion. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of Emotion(pp. 119–142). New York: Guilford Press.

    Google Scholar 

  • Cañamero, D. (1997). Modelling motivations and emotions as a basis for intelligent behavior. InProceedings of International Conference on Autonomous Agents, Marina del Rey, CA (pp. 148– 155).

    Google Scholar 

  • Cassell, J., Nakano, Y., Bickmore, T., Sidner, C.,&Rich, C. (2001a). Non-verbal cues for discourse structure.Association for Computational Linguistics Joint EACL — ACL Conference(pp. 106– 115).

    Google Scholar 

  • Cassell, J., Vilhjalmsson, H.,&Bickmore, T. (2001b). BEAT: The behavior expression animation toolkit. InProceedings of SIGGRAPH(pp. 477–486).

    Google Scholar 

  • Corraze, G. (1980).Les communications nonverbales. Paris: Presses Universitaires de France.

    Google Scholar 

  • Cosmides, L. (1983). Invariances in the acoustic expressions of emotions during speech.Journal of Experimental Psychology, Human Perception Performance,9, 864–881

    Article  Google Scholar 

  • Damasio, A. R., Grabowski, T. J., Bechara, A., Damasio, H., Ponto, L. B., Parvizi, J.,&Hichwa, R. D. (2000). Subcortical and cortical brain activity during the feeling of self-generated emotions.Nature Neuroscience,3, 1049–1056.

    Article  Google Scholar 

  • Doyle, P. (1999). When is a communicative agent a good idea? InProceedings of International Workshop on Communicative and Autonomous Agents, Seattle (pp. 1–2).

    Google Scholar 

  • Edwards, G. J., Cootes, T. F.,&Taylor, C. J. (1998). Face recognition using active appearance models. InProceedings of the European Conference on Computer Vision,2, 581–695.

    Google Scholar 

  • Ekman, P. (1984). Expression and the nature of emotion. In K. Scherer&P. Ekman (Eds.),Approaches to emotion(pp. 319–343). Hillsdale, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Ekman, P. (1989). The argument and evidence about universals in facial expressions of emotion. In H. Wagner&A. Manstead (Eds.),Handbook of social psychophysiology(pp. 143–164). Chichester: Wiley.

    Google Scholar 

  • Ekman, P. (1992a). Facial expression of emotion: New findings, new questions.Psychological Science,3, 34–38.

    Article  Google Scholar 

  • Ekman, P. (1992b). An argument for basic emotions.Cognition and Emotion,6, 169–200.

    Article  Google Scholar 

  • Ekman, P.,&Friesen, W. V. (1967). Head and body cues in the judgement of emotion: A reformulation.Perceptual Motor Skills 24, 711–724.

    Google Scholar 

  • Ekman, P.,&Friesen, W. V. (1977).Manual for the facial action coding system. Palo Alto: Consulting Psychologists Press.

    Google Scholar 

  • Ekman, P.,&Friesen, W. V. (1978).Facial action coding system: A technique for the measurement of facial movement. Palo Alto, CA: Consulting Psychologists Press.

    Google Scholar 

  • Ekman, P., Friesen, W. V.,&Hager, J. C. (2002).The facial action coding system(2nd ed.). Salt Lake City: Weidenfeld&Nicolson.

    Google Scholar 

  • Elliott, C. D. (1992). The affective reasoner: A process model of emotions in a multi-agent system. Ph.D. Thesis, Institute for the Learning Sciences, Northwestern University, Evanston, Illinois

    Google Scholar 

  • Esposito, A. (2000). Approaching speech signal problems: An unifying viewpoint for the speech recognition process. In S. Suarez Garcia&R. Baron Fernandez (Eds.),Memoria of Taller Internacional de Tratamiento del Habla, Procesamiento de Vos y el Language. CIC—IPN Obra Compleata, Mexico.

    Google Scholar 

  • Esposito, A. (2002). The importance of data for training intelligent devices. In B. Apolloni&C. Kurfess (Eds.),From synapses to rules: Discovering symbolic knowledge from neural processed data(pp. 229–250). Dordrecht: Kluwer Academic Press.

    Google Scholar 

  • Esposito, A. (2007a). The amount of information on emotional states conveyed by the verbal and nonverbal channels: Some perceptual data. In Y. Stilianou et al. (Eds.),Progress in nonlinear speech processing(LNCS 4392, pp. 245–264), New York: Springer-Verlag.

    Google Scholar 

  • Esposito, A. (2007b). COST 2102: Cross-modal analysis of verbal and nonverbal communication (CAVeNC). In A. Esposito et al. (Eds.),Verbal and nonverbal communication behaviours(LNCS, 4775, pp. 1–10). New York: Springer-Verlag.

    Chapter  Google Scholar 

  • Esposito, A., Duncan S.,&Quek F. (2002): Holds as gestural correlated to empty and filled pauses. InProceedings of ICSLP,1(pp. 541–544).

    Google Scholar 

  • Esposito, A., Esposito, D., Refice, M., Savino, M.,&Shattuck-Hufnagel, S. (2007). A preliminary investigation of the relationships between gestures and prosody in Italian. In A. Esposito et al. (Eds.),Fundamentals of verbal and nonverbal communication and the biometric issue. NATO Publishing Series, Human and Societal Dynamics (18, pp. 4164–4174). The Netherlands: IOS Press.

    Google Scholar 

  • Esposito, A., Esposito, D.,&Trojano, L. (2007). Gestures, pauses, and aphasia: Four study cases. InProceedings of the IEEE International Symposium on Research on Assistive Technologies, Dayton, OH, April 16 (pp. 59–63).

    Google Scholar 

  • Esposito, A., Gutierrez-Osuna, R., Kakumanu, P., Garcia, O.N. (2002). Optimal data encoding for speech driven facial animation. Wright State University Tech. Rep. N. CS-WSU-04-02, Dayton, OH.

    Google Scholar 

  • Esposito, A.,&Marinaro, M. (2007). What pauses can tell us about speech and gesture partnership. In A. Esposito et al. (Eds.),Fundamentals of verbal and nonverbal communication and the biometric issue, NATO Publishing Series, Human and Societal Dynamics (18, pp. 45–57). The Netherlands: IOS Press.

    Google Scholar 

  • Esposito, A., McCullough K. E., Quek F. (2001). Disfluencies in gesture: Gestural correlates to filled and unfilled speech pauses. InProceedings of IEEE Workshop on Cues in Communication, Hawai, December 9 (pp. 1–6).

    Google Scholar 

  • Ezzat T., Geiger G.,&Poggio, T. (2002). Trainable videorealistic speech animation. InProceedings of SIGGRAPH, San Antonio, TX, July (pp. 388–397).

    Google Scholar 

  • Fasel, B.,&Luettin, J. (2003). Automatic facial expression analysis: A survey.Pattern Recognition,36, 259–275.

    Article  MATH  Google Scholar 

  • Feyereisen, P. (1983). Manual activity during speaking in aphasic subjects.International Journal of Psychology,18, 545–556.

    Article  Google Scholar 

  • Frick, R. (1985). Communicating emotions: The role of prosodic features.Psychological Bulletin,93, 412–429.

    Article  Google Scholar 

  • Friend, M. (2000). Developmental changes in sensitivity to vocal paralanguage.Developmental Science,3, 148–162.

    Article  Google Scholar 

  • Frijda, N. H. (1986).The emotions. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Frijda, N. H. (1993). Moods, emotion episodes, and emotions. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of emotion(pp. 381–402). New York: Guilford Press.

    Google Scholar 

  • Fu, S., Gutierrez-Osuna, R., Esposito, A., Kakumanu, P.,&Garcia, O. N. (2005). Audio/visual mapping with cross-modal hidden Markov models.IEEE Transactions on Multimedia,7(2), 243–252.

    Article  Google Scholar 

  • Fulcher, J. A. (1991). Vocal affect expression as an indicator of affective response.Behavior Research Methods, Instruments,&Computers,23, 306–313.

    Google Scholar 

  • Gallager, R. G. (1968).Information theory and reliable communication. New York: John Wiley&Sons.

    MATH  Google Scholar 

  • Goldin-Meadow, S. (2003).Hearing gesture: How our hands help us think. Cambridge, MA: Belk-nap Press at Harvard University Press.

    Google Scholar 

  • Graham, J., Ricci-Bitti, P. E.,&Argyle, M. (1975). A cross-cultural study of the communication of emotion by facial and gestural cues.Journal of Human Movement Studies,1, 68–77.

    Google Scholar 

  • Gutierrez-Osuna, R., Kakumanu, P., Esposito, A., Garcia, O.N., Bojorquez, A., Castello, J.,&Rudomin I. (2005). Speech-driven facial animation with realistic dynamic.IEEE Transactions on Multimedia,7(1), 33–42.

    Article  Google Scholar 

  • Hozjan, V.,&Kacic, Z. (2003). Context-independent multilingual emotion recognition from speech signals.International Journal of Speech Technology,6, 311–320.

    Article  Google Scholar 

  • Hozjan, V.,&Kacic, Z. (2006). A rule-based emotion-dependent feature extraction method for emotion analysis from speech.Journal of the Acoustical Society of America,119(5), 3109– 3120.

    Article  Google Scholar 

  • Huang, C. L.,&Huang, Y. M. (1997). Facial expression recognition using model-based feature extraction and action parameters classification.Journal of Visual Commumication and Image Representation,8(3), 278–290.

    Article  Google Scholar 

  • Izard, C. E. (1979). The maximally discriminative facial movement coding system (MAX). Unpublished manuscript. Available from Instructional Resource Center, University of Delaware.

    Google Scholar 

  • Izard, C. E. (1992). Basic emotions, relations among emotions, and emotion—cognition relations.Psychological Review,99, 561–565.

    Article  Google Scholar 

  • Izard, C. E. (1993). Organizational and motivational functions of discrete emotions. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of emotions(pp. 631–641). New York: Guilford Press.

    Google Scholar 

  • Izard, C. E. (1994). Innate and universal facial expressions: Evidence from developmental and cross-cultural research.Psychological Bulletin,115, 288–299.

    Article  Google Scholar 

  • Izard, C. E., Dougherty, L. M.,&Hembree, E. A. (1983). A system for identifying affect expressions by holistic judgments. Unpublished manuscript. Available from Instructional Resource Center, University of Delaware.

    Google Scholar 

  • Kähler K., Haber, J.,&Seidel, H. (2001). Geometry-based muscle modeling for facial animation. InProceedings of the International Conference on Graphics Interface(pp. 27–36).

    Google Scholar 

  • Kakumanu, P. (2006). Detecting faces and recognizing facial expressions. PhD thesis. Wright State University, CSE Department, Dayton, OH.

    Google Scholar 

  • Kakumanu, P., Esposito, A., Garcia, O. N.,&Gutierrez-Osuna, R. (2006). A comparison of acoustic coding models for speech-driven facial animation.Speech Commumication,48, 598–615.

    Article  Google Scholar 

  • Kakumanu, P., Gutierrez-Osuna R., Esposito, A., Bryll, R., Goshtasby A.,&Garcia, O. N. (2001). Speech driven facial animation. InProceedings of ACM Workshop on Perceptive User Interfaces, Orlando, 15–16 November (pp. 1–4).

    Google Scholar 

  • Kanade, T., Cohn, J.,&Tian, Y. (2000). Comprehensive database for facial expression analysis. InProceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition(pp. 46–53).

    Google Scholar 

  • Kendon, A. (2004).Gesture: Visible action as utterance. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Klasmeyer, G.,&Sendlmeier W. F. (1995). Objective voice parameters to characterize the emotional content in speech. In K. Elenius&P. Branderudf (Eds.),Proceedings of ICPhS 1995, (1, pp. 182–185). Arne Strömbergs Grafiska, Stockholm.

    Google Scholar 

  • Koda, T. (1996). Agents with faces: A study on the effect of personification of software agents. Masters thesis, MIT Media Lab, Cambridge, MA, Stockholm.

    Google Scholar 

  • Krauss, R., Chen, Y.,&Gottesman, R. F. (2000). Lexical gestures and lexical access: A process model. In D. McNeill (Ed.),Language and gesture(pp. 261–283). UK: Cambridge University Press.

    Google Scholar 

  • Krauss, R., Morrel-Samuels, P.,&Colasante, C. (1991). Do conversational hand gestures communicate?Journal of Personality and Social Psychology,61(5), 743–754.

    Article  Google Scholar 

  • Levenson, R. W. (1992). Autonomic nervous system differences among emotions.Psychological Science,3, 23–27.

    Article  Google Scholar 

  • Levenson, R. W. (1994). Human emotion: A functional view. In P. Ekman&R. J. Davidson (Eds.),The nature of emotion: Fundamental questions(pp. 123–126). New York: Oxford University Press.

    Google Scholar 

  • Littlewort, G., Bartlett, M. S., Fasel, I., Susskind, J.,&Movellan, J. R. (2004). Dynamics of facial expression extracted automatically from video. InIEEE Conference on Computer Vision and Pattern Recognition, http://citeseer.ist.psu.edu/711804.html.

  • MacLean, P. (2000). Cerebral evolution of emotion. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of emotions(pp. 67–83). New York: Guilford Press.

    Google Scholar 

  • Massaro, D. W. (1998).Perceiving talking faces. Cambridge, MA: MIT Press.

    Google Scholar 

  • McNeill, D. (2005).Gesture and thought. Chicago: University of Chicago Press.

    Google Scholar 

  • Morishima, S. (2001). Face analysis and synthesis.IEEE Signal Processing Magazine,18(3), 26–34.

    Article  Google Scholar 

  • Navas, E., Hernáez, I.,&Luengo, I. (2006). An objective and subjective study of the role of semantics and prosodic features in building corpora for emotional TTS.IEEE Transactions on Audio, Speech, and Language Processing,14(4), 1117–1127.

    Article  Google Scholar 

  • Nushikyan, E. A. (1995). Intonational universals in texual context. In K. Elenius&P. Branderudf (Eds.),Proceedings of ICPhS 1995 (1, pp. 258–261). Arne Strömbergs Grafiska, Stockholm.

    Google Scholar 

  • Oatley, K., Jenkins, J. M. (2006).Understanding emotions(2nd ed.). Oxford, England: Blackwell.

    Google Scholar 

  • Ostermann, J. (1998). Animation of synthetic face in MPEG-4. InProceedings of Computer Animation(pp. 49–51). Philadelphia, June 8–10.

    Google Scholar 

  • Overview of the MPEG-4 Standard (1999). ISO/IEC JTC1/SC29/WG11 M2725, Seoul, South Korea.

    Google Scholar 

  • Panksepp, J. (2000). Emotions as natural kinds within the mammalian brain. In J. M. Lewis and M. Haviland-Jones (Eds.),Handbook of emotions(2nd ed., pp. 137–156). New York: Guilford Press.

    Google Scholar 

  • Panksepp, J. (2003). At the interface of the affective, behavioral, and cognitive neurosciences: Decoding the emotional feelings of the brain.Brain and Cognition 52, 4–14.

    Article  Google Scholar 

  • Pantic, M., Patras, I.,&Rothkrantz, J. M. (2002). Facial action recognition in face profile image sequences. InProceedings IEEE International Conference Multimedia and Expo(pp. 37–40).

    Google Scholar 

  • Pantic, M.,&Rothkrantz, J. M. (2000). Expert system for automatic analysis of facial expression.Image and Vision Computing Journal,18(11), 881–905.

    Article  Google Scholar 

  • Petkov, N.,&Wieling, M. B. (2004). Gabor filtering augmented with surround inhibition for improved contour detection by texture suppression.Perception,33, 68c.

    Google Scholar 

  • Phillips, P. J., Flynn, P. J., Scruggs, T.,&Bowyer, K. W. (2005) Overview of the face recognition grand challenge. InProceedings of IEEE Conference on Computer Vision and Pattern Recognition.

    Google Scholar 

  • Pittam J.,&Scherer K. R. (1993). Vocal expression and communication of emotion. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of emotion(pp. 185–197). New York: Guilford Press.

    Google Scholar 

  • Plutchik, R. (1966). Emotions as adaptive reactions: Implications for therapy.Psychoanalytic Review, LIII,2: 105–110.

    Google Scholar 

  • Plutchik, R. (1993). Emotion and their vicissitudes: Emotions and psychopatology. In J. M. Lewis&M. Haviland-Jones (Eds.),Handbook of Emotion(pp. 53–66). New York: Guilford Press.

    Google Scholar 

  • Rosenberg, B. G.,&Langer, J. (1965). A study of postural gestural communication.Journal of Personality and Social Psychology 2(4), 593–597.

    Article  Google Scholar 

  • Roth, D., Yang, M.,&Ahuja, N. (2000). A snow-based face detector.Advances in Neural Information Processing Systems,12, 855–861.

    Google Scholar 

  • Russell, J. A. (1980). A circumplex model of affect.Journal of Personality and Social Psychology,39, 1161–1178.

    Article  Google Scholar 

  • Scherer, K. (2003). Vocal communication of emotion: A review of research paradigms.Speech Communication 40, 227–256.

    Article  MATH  Google Scholar 

  • Scherer, K. R. (1982).Experiencing emotion: A cross-cultural study, Cambridge: Cambridge University Press.

    Google Scholar 

  • Scherer, K. R. (1989). Vocal correlates of emotional arousal and affective disturbance. In H. Wagner,&A. Manstead (Eds.)Handbook of social psychophysiology(pp. 165–197). New York: Wiley UK.

    Google Scholar 

  • Scherer, K. R., Banse, R.,&Wallbott, H. G. (2001). Emotion inferences from vocal expression correlate across languages and cultures.Journal of Cross-Cultural Psychology,32, 76–92.

    Article  Google Scholar 

  • Scherer, K. R., Banse, R., Wallbott, H. G.,&Goldbeck, T. (1991). Vocal cues in emotion encoding and decoding.Motivation and Emotion,15, 123–148.

    Article  Google Scholar 

  • Scherer, K. R.,&Oshinsky, J. S. (1977). Cue utilization in emotion attribution from auditory stimuli.Motivation and Emotion,1, 331–346.

    Article  Google Scholar 

  • Schlosberg, H. (1953). Three dimensions of emotion.Psychological Review,61(2), 81–88.

    Article  Google Scholar 

  • Schwartz, G. E., Ahern, G. L.,&Brown, S. (1979). Lateralized facial muscle response to positive and negative emotional stimuli.Psychophysiology,16, 561–571.

    Article  Google Scholar 

  • Schwartz, G. E., Fair, P. L., Salt, P., Mandel, M. R.,&Klerman, G. L. (1976). Facial muscle patterning to affective imagery in depressed and non-depressed subjects.Science,192, 489– 491.

    Article  Google Scholar 

  • Schwartz, G. E., Weinberger, D. A.,&Singer, J. A. (1981). Cardiovascular differentiation of happiness, sadness, anger, and fear following imagery and exercise.Psychosomatic Medicine,43, 343–364.

    Google Scholar 

  • Shannon, C. E.,&Weaver, W. (1949).Mathematical theory of communication. Chicago, USA: University of Illinois Press.

    MATH  Google Scholar 

  • Sinanovic, S.,&Johnson, D. H. (2007). Toward a theory of information processing.Signal Processing,87, 1326–1344, http://www-ece.rice.edu/~dhj/cv.html#publications.

    Article  Google Scholar 

  • Stocky, T.,&Cassell, J. (2002). Shared reality: Spatial intelligence in intuitive user interfaces. InProceedings of Intelligent User Interfaces(pp. 224–225), San Francisco.

    Google Scholar 

  • Tekalp. M.,&Ostermann J. (2000). Face and 2-D mesh animation in MPEG-4.Signal Processing and Image Communication,15, 387–421.

    Article  Google Scholar 

  • Viola A, P.,&Jones, M. J. (2004). Robust real-time face detection.International Journal of Computer Vision 57(2), 137–154.

    Article  Google Scholar 

  • Zadeh, L. A. (1988). Fuzzy logic.IEEE Computer,21(4), 83–93.

    Google Scholar 

  • Zhao, W., Chellappa, R., Phillips, P. J.,&Rosenfeld, A. (2003). Face recognition: A literature survey.ACM Computing Surveys,35(4), 399–458.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Psicologia, Seconda Universit di Napoli Via Vivaldi 43, Caserta, 81100, Italy

    Anna Esposito

  2. IIASS, Via Pellegrino 19, Vietri sul Mare, SA, 84019, Italy

    Anna Esposito

Authors
  1. Anna Esposito
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Haidian, Beijing, 100080, P.R. China

    Jianhua Tao  & Tieniu Tan BSc, MSc, PhD  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag London Limited

About this chapter

Cite this chapter

Esposito, A. (2009). Affect in Multimodal Information. In: Tao, J., Tan, T. (eds) Affective Information Processing. Springer, London. https://doi.org/10.1007/978-1-84800-306-4_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-84800-306-4_12

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-305-7

  • Online ISBN: 978-1-84800-306-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation