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2014 | 2 | 85--91
Tytuł artykułu

An unorthodox view on the problem of tracking facial expressions

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Recent developments in imaging cameras has opened a new way of analyzing facial expression. We would like to take advantage from this new technology and present a method of imaging and processing images of human face as a response to the particular stimuli. The response in this case is represented by the facial expressions and the stimuli are still images representing six basic emotions according to Eckmann. Working hypothesis of presented research, states that the new method of tracking facial expressions is more precise and distinctive enough to give characteristic description of the analyzed human face. The biggest advantage of the presented method, in the opinion of research team, is the fact that it uses remote sensing techniques and presents dynamics of the changes happening on the human face. Therefore, FMRI might not be required, which decreases the costs of experiments, additionally, method is less stressful for the examined persons and provides more natural reactions.(original abstract)
Rocznik
Tom
2
Strony
85--91
Opis fizyczny
Twórcy
  • University of Gdansk, Poland
  • University of Gdansk, Poland
  • University of Warmia and Mazury in Olsztyn, Poland
  • Gdansk University of Technology, Poland
  • Gdansk University of Technology, Poland
  • Gdansk University of Technology, Poland
Bibliografia
  • Agrafioti F., Hatzinakos D., and Anderson A. K., "ECG Pattern Analysis for Emotion Detection," IEEE Transactions on Affective Computing, vol. 3, no. 1, pp. 102-115, Jan. 2012. [Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5999653
  • Balomenos T., Raouzaiou A., Ioannou S., Drosopoulos A., Karpouzis K., Kollias S., "Emotion Analysis in Man-Machine Interaction Systems," in in Proc. MLMI, LNCS 3361, 2005, pp. 318-328.
  • Cao Y., Zheng W., Zhao L., and Zhou C., "LNCS 3784 - Expression Recognition Using Elastic Graph Matching," Lecture Notes in Computer Science, vol. 3784, pp. 8-15, 2005.
  • Ekman P. and Hager J. C., "Computer Measurement of Sign Vehicles in Body Movement and Facial Expression." [Online]. Available: http://face-and-emotion.com/dataface/misctext/iwafgr.html
  • Ekman P., Friesen W. V., and Hager J. C., "Facial Action Coding System - Title Page," 666 Malibu Drive, Salt Lake City UT 84107, Tech. Rep., 2002. [Online]. Available: http: //face-and-emotion.com/dataface/facs/manual/TitlePage.html
  • Fasel B. and Luettin J., "Automatic facial expression analysis: a survey," Pattern Recognition, vol. 36, no. 1, pp. 259-275, Jan. 2003. [Online]. Available: http://linkinghub.elsevier.com/retrieve/pii/S0031320302000523
  • Ghimire D. and Lee J., "Geometric Feature-Based Facial Expression Recognition in Image Sequences Using Multi-Class AdaBoost and Support Vector Machines." Sensors (Basel, Switzerland), vol. 13, no. 6, pp. 7714-34, Jan. 2013. [Online]. Available: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3715259\&tool=pmcentrez\&rendertype=abstract
  • Guo G., Guo R., and Li X., "Facial Expression Recognition Influenced by Human Aging," IEEE Transactions on Affective Computing, vol. 4, no. 3, pp. 291-298, Jul. 2013. [Online]. Available: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6517179
  • Gur R. C., Sara R., Hagendoorn M., Marom O., Hughett P., Macy L., Turner T., Bajcsy R., Posner A., and Gur R. E., "A method for obtaining 3-dimensional facial expressions and its standardization for use in neurocognitive studies." Journal of neuroscience methods, vol. 115, no. 2, pp. 137-43, Apr. 2002. [Online]. Available: http://www.ncbi.nlm.nih.gov/pubmed/11992665
  • Heylen D., Ghijsen M., Nijholt A., and Akker R. D., "Facial Signs of Affect During Tutoring Sessions," pp. 24-31, 2005.
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  • Laeng B. and Sulutvedt U., "The eye pupil adjusts to imaginary light." Psychological science, vol. 25, no. 1, pp. 188-97, Jan. 2014. [Online]. Available: http://pss.sagepub.com/content/25/1/188
  • Pantic M. and Bartlett M. S., Machine Analysis of Facial Expressions, 2007, no. June.
  • Pfister T., Li X., Zhao G., and Pietik M., "Recognising Spontaneous Facial Micro-expressions."
  • Picard R. W., "Emotion Research by the People, for the People," Emotion Review, vol. 2, no. 3, pp. 250-254, Jun. 2010. [Online]. Available: http://emr.sagepub.com/cgi/doi/10.1177/1754073910364256
  • Picard R. W., Member S., Vyzas E., and Healey J., "Toward Machine Emotional Intelligence : Analysis of Affective Physiological State," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 23, no. 10, pp. 1175-1191, 2001.
  • Pratt W. K., Digital Image Processing. New York, USA: John Wiley & Sons, Inc., 2001. [Online]. Available: http://doi.wiley.com/10.1002/0471221325
  • Raffel M., Willert C. E., Kompenhans J., Particle Image Velocimetry: A Practical Guide ; with 24 Tables, 1998. [Online]. Available: http://www.google.pl/books?hl=pl\&lr=\&id=enOLTmfYVPQC\&pgis=1
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  • Tao J., Tan T., Picard R., A. Choi, and W. Woo, Affective Computing and Intelligent Interaction, ser. Lecture Notes in Computer Science, A. C. R. Paiva, R. Prada, and R. W. Picard, Eds. Springer Berlin Heidelberg, 2007, vol. 4738, no. September. [Online]. Available: http://www.springerlink.com/index/10.1007/978-3-540-74889-2
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171323143

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