EmEx, a tool for automated emotive face recognition using convolutional neural networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 10406 LNCS, Issue , 2017, Pages 692-704

  Riganelli, Matteo ^a   Franzoni, Valentina ^b   Gervasi, Osvaldo ^a   Tasso, Sergio ^a  

^a UNIVERSITY OF PERUGIA   (Italy)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Emotion recognition; Face detection; Image; Machine learning CNN; Recognition

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUGMENTED REALITY; CONVOLUTION; LEARNING SYSTEMS; MOBILE DEVICES; NEURAL NETWORKS; SPEECH RECOGNITION;

CONVOLUTIONAL NEURAL NETWORK; EMOTION RECOGNITION; HEALTH-CARE MANAGEMENTS; IMAGE; MACHINE LEARNING APPROACHES; OPEN-SOURCE LIBRARIES; RECOGNITION; VISUAL RECOGNITION;

FACE RECOGNITION;

EID: 85026755482     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-62398-6_49     Document Type: Conference Paper

References (47)

1. Mahalanobis, P.C.: On the generalised distance in statistics. Proc. Natl. Inst. Sci. India 2(1), 49–55 (1936)
2. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models-their training and application. Comput. Vis. Image Underst. 61(1), 38–59 (1995). ISSN: 1077-3142
3. Stiefelhagen, R., Yang, J., Waibel, A.: A model-based gaze tracking system. Int. J. Artif. Intell. Tools 6(2), 193–209 (1997)
4. Levenshtein, V.I.: Binary Codes Capable of Correcting Deletions, Insertions and Reversals, vol. 10, p. 707. Soviet Physics Doklady (1966)
5. Pigeon, S., Vandendorpe, L.: The M2VTS multimodal face database (Release 1.00). In: Bigün, J., Chollet, G., Borgefors, G. (eds.) AVBPA 1997. LNCS, vol. 1206, pp. 403–409. Springer, Heidelberg (1997). doi:10.1007/BFb0016021
6. Picard, R.W., Vyzas, E., Healey, J.: Toward machine emotional intelligence: analysis of affective physiological state. IEEE Trans. Pattern Anal. Mach. Intell. 23(10), 1175–1191 (2001)
7. Picard, R.W.: Affective computing: challenges. Int. J. Hum. Comput. Stud. 59(1–2), 55–64 (2003)
8. Eveno, N., Caplier, A., Coulon, P.Y.: Accurate and quasi-automatic lip tracking. IEEE Trans. Circuits Syst. Video Technol. 14(5), 706–715 (2004). ISSN: 1051-8215
9. Franzoni, V., Gervasi, O.: Guidelines for web usability and accessibility on the Nintendo Wii. In: Gavrilova, M.L., Tan, C.J.K. (eds.) Transactions on Computational Science VI. LNCS, vol. 5730, pp. 19–40. Springer, Heidelberg (2009). doi:10.1007/978-3-642-10649-1 2
10. Lombardi, L., ur Rehman Butt, W., Grecuccio, M.: Lip tracking towards an automatic lip reading approach. JMPT 5, 1–11 (2014)
11. Gervasi, O., Magni, R., Zampolini, M.: Nu!RehaVR: Virtual reality in neuro tele-rehabilitation of patients with traumatic brain injury and stroke. Virtual Reality 14(2), 131–141 (2010)
12. Saeed, U., Dugelay, J.-L.: Combining edge detection and region segmentation for lip contour extraction. In: Proceedings of the 6th Conference on Articulated Motion and Deformable Objects, AMDO 2010, Andratx, Mallorca, Spain, 7–9 July 2010. Also published in LNCS, vol. 6169 (2010)
13. Hayes, G.R., Hirano, S., Marcu, G., Monibi, M., Nguyen, D.H., Yeganyan, M.: Interactive visual supports for children with autism. Pers. Ubiquit. Comput. 14(7), 663–680 (2010)
14. Pantelopoulos, A., Bourbakis, N.G.: A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 40(1), 1–12 (2010). Art. no. 5306098
15. Chmiel, A., Sienkiewicz, J., Thelwall, M., Paltoglou, G., Buckley, K., Kappas, A., Ho̷lyst, J.A.: Collective emotions online and their influence on community life. PLoS ONE 6(7) (2011). Art. no. e22207
16. Krizhevsky, A., Sutskever, I., Hinton, G.: ImageNet classification with deep convolutional neural networks. In: Advance in Neural Information Processing System, vol. 25, pp. 1106–1114 (2012)
17. Gervasi, O., Russo, D., Vella, F.: The AES implantation based on OpenCL for multi/many core architecture. In: 2010 International Conference on Computational Science and Its Applications, Fukuoka, ICCSA 2010, pp. 129–134. IEEE Computer Society, Washington, DC (2010). doi:10.1109/ICCSA.2010.44
18. Vella, F., Neri, I., Gervasi, O., Tasso, S.: A simulation framework for scheduling performance evaluation on CPU-GPU heterogeneous system. In: Murgante, B., Gervasi, O., Misra, S., Nedjah, N., Rocha, A.M.A.C., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2012. LNCS, vol. 7336, pp. 457–469. Springer, Heidelberg (2012). doi:10.1007/978-3-642-31128-4 34
19. Mariotti, M., Gervasi, O., Vella, F., Cuzzocrea, A., Costantini, A.: Strategies and systems towards grids and clouds integration: a DBMS-based solution. Future Gener. Comput. Syst. (2017). doi:10.1016/j.future.2017.02.047
20. Neumann, M., Patricia, N., Garnett, R., Kersting, K.: Efficient graph kernels by randomization. In: Flach, P.A., Bie, T., Cristianini, N. (eds.) ECML PKDD 2012. LNCS, vol. 7523, pp. 378–393. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33460-3 30
21. Cheng, V.C., Leung, C.H.C., Liu, J., Milani, A.: Probabilistic aspect mining model for drug reviews. IEEE Trans. Knowl. Data Eng. 26(8), 2002–2013 (2014). Art. no. 6678354
22. Franzoni, V., Poggioni, V., Zollo, F.: Automated classification of book blurbs according to the emotional tags of the social network Zazie. In: CEUR Workshop Proceedings, vol. 1096, pp. 83–94 (2013)
23. Bertola, F., Patti, V.: Emotional responses to artworks in online collections. In: CEUR Workshop Proceedings, vol. 997 (2013)
24. Saif, H., Fernandez, M., He, Y., Alani, H.: Evaluation datasets for Twitter sentiment analysis a survey and a new dataset, the STS-Gold. In: CEUR Workshop Proceedings, vol. 1096, pp. 9–21 (2013)
25. Cieliebak, M., Dürr, O., Uzdilli, F.: Potential and limitations of commercial sentiment detection tools. In: CEUR Workshop Proceedings, vol. 1096, pp. 47–58 (2013)
26. Tasso, S., Pallottelli, S., Rui, M., Laganá, A.: Learning objects efficient handling in a federation of science distributed repositories. In: Murgante, B., et al. (eds.) ICCSA 2014. LNCS, vol. 8579, pp. 615–626. Springer, Cham (2014). doi:10.1007/978-3-319-09144-0 42
27. Karayev, S., Trentacoste, M.: Recognizing Image Style. University of California Barkley Adobe, Helen Han (2014)
28. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015). doi:10.1038/nature14539. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. ISBN: 0028-0836
29. Patel, V.M., Gopalan, R., Li, R., Chellappa, R.: Visual domain adaptation: a survey of recent advances. IEEE Signal Process. Mag. 32(3), 53–69 (2015). Art. no. 7078994
30. Peng, K.-C., Chen, T., Sadovnik, A., Gallagher, A.: A mixed bag of emotions: model, predict, and transfer emotion distributions. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 07– 12 June 2015, pp. 860–868 (2015). Art. no. 7298687
31. Baioletti, M., Milani, A., Santucci, V.: Linear ordering optimization with a combinatorial differential evolution. In: 2015 IEEE Proceedings of the International Conference on Systems, Man, and Cybernetics, SMC 2015, pp. 2135–2140 (2016). Art. no. 7379505
32. Voirin, N., Payet, C., Barrat, A., Cattuto, C., Khanafer, N., Régis, C., Kim, B.-A., Comte, B., Casalegno, J.-S., Lina, B., Vanhems, P.: Combining high-resolution contact data with virological data to investigate influenza transmission in a tertiary care hospital. Infect. Control Hosp. Epidemiol. 36(3), 254–260 (2015)
33. Phelan, I., Arden, M., Garcia, C., Roast, C. Exploring virtual reality and prosthetic training. In: 2015 IEEE Virtual Reality Conference, VR 2015 - Proceedings, pp. 353–354 (2015). Art. no. 7223441
34. Costarelli, D., Vinti, G.: Max-product neural network and quasi-interpolation operators activated by sigmoidal functions. J. Approx. Theory 209, 1–22 (2016)
35. Franzoni, V., Milani, A., Pallottelli, S., Leung, C.H.C., Li, Y. Context-based image semantic similarity. In: 2015 Proceedings of the 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015, pp. 1280–1284 (2016). Art. no. 7382127
36. Lewis, T.W., Powers, D.M.W.: Lip contour detection techniques based on front view of face. J. Glob. Res. Comput. Sci. 2(5), 43–46 (2011). ISSN: 2229-371X
37. Gervasi, O., Magni, R., Ferri, M.: A method for predicting words by interpreting labial movements. In: Gervasi, O., et al. (eds.) ICCSA 2016. LNCS, vol. 9787, pp. 450–464. Springer, Cham (2016). doi:10.1007/978-3-319-42108-7 34
38. Bastianelli, E., Nardi, D., Aiello, L.C., Giacomelli, F., Manes, N.: Speaky for robots: the development of vocal interfaces for robotic applications. Appl. Intell. 44(1), 43–66 (2016)
39. Biondi, G., Franzoni, V., Li, Y., Milani, A.: Web-based similarity for emotion recognition in web objects. In: Proceedings of the 9th International Conference on Utility and Cloud Computing, UCC 2016, Shanghai, China, 6–9 December 2016, pp. 327–332 (2016)
40. Alkuhlani, A., Nassef, M., Farag, I.: Multistage feature selection approach for high-dimensional cancer data. Soft Comput., 1–12 (2016)
41. Canossa, A., Badler, J., El-Nasr, M.S., Anderson, E.: Eliciting emotions in design of games - a theory driven approach. In: CEUR Workshop Proceedings, vol. 1680, pp. 34–40 (2016)
42. Caffe Framework - Github.https://github.com/BVLC/caffe
43. Lou, Y., Wu, W., Vatavu, R.-D., Tsai, W.T.: Personalized gesture interactions for cyber-physical smart-home environments. Sci. China Inf. Sci. 60(7), 072104 (2017)
44. Franzoni, V., Chiancone, A., Milani, A.: A multistrain bacterial diffusion model for link prediction. Int. J. Pattern Recognit. Artif. Intell. 31(11) (2017). World Scientific. doi:10.1142/S0218001417590248
45. Cui, W., Du, Y., Shen, Z., Zhou, Y., Li, J.: Personalized microblog recommendation using sentimental features. In: 2017 IEEE International Conference on Big Data and Smart Computing, BigComp 2017, pp. 455–456 (2017). Art. no. 7881756
46. Angelov, P., Gu, X., Iglesias, J.A., Ledezema, A., et al.: Cybernetics of the mind, learning individual’s perceptions autonomously. IEEE Syst. Man Cybern. 3(1), 8–21 (2017)
47. Franzoni, V., Milani, A., Vallverdu, J.: Emotional affordances in human-machine interactive planning and negotiation. In: Proceedings of WI 2017, Workshop on Affective Computing and Emotion Recognition (ACER) (2017)