Abstract
This paper specifically focuses on how to build a Chinese facial expression database collecting the facial expressions of college students and describes a strategy to develop an automatically detecting technique for academic emotions to support teachers making better decisions in blended and digital learning environments. There are some famous worldwide databases of facial emotion expressions, e.g., Amsterdam Dynamic Facial Expression Set (ADFES), Montreal set of facial displays of emotion, or Brazillian FEI database. Their major collections are full facial expression of western people with very limited Asian or Chinese faces. Because some emotion facial expressions might be culturally bounded, it arises the necessity to develop a Chinese facial expression database as a critical step to develop an automatically facial emotion expression dictating technique with high accuracy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Izard, C.E.: The Psychology of Emotions. Plenum, New York (1991)
Buck, R.: Social factors in facial display and communication: a reply to Chovil and others. J. Nonverbal Behav. 15, 155–162 (1991)
Kobayashi, H., Hara, F.: Real time dynamic control of 6 basic facial expressions on face robot. J. Robot. Soc. Japan 14(5), 677–685 (1996)
Ekman, P.: Emotional and conversational nonverbal signals. In: Larrazabal, J.M., Miranda, L.A.P. (eds.) Language, Knowledge, and Representation. Philosophical Studies Series, vol. 99, pp. 39–50. Springer, Dordrecht (2004). https://doi.org/10.1007/978-1-4020-2783-3_3
Pekrun, R., Goetz, T., Titz, W., Perry, R.P.: Academic emotions in students’ self-regulated learning and achievement: a program of qualitative and quantitative research. Educ. Psychol. 37(2), 91–105 (2002)
Matsumoto, D., Hwang, H.C.: Judgments of subtle facial expressions of emotion. Emotion 14(2), 349–357 (2014)
Wu, B., Lin, C.: Adaptive feature mapping for customizing deep learning based facial expression recognition model. IEEE Access 6, 12451–12461 (2018)
Ekman, P., Friesen, W.V.: Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto (1978)
Ekman, P.: Facial expression and emotion. Am. Psychol. 48, 384–392 (1993)
Chen, Y.-M.: A deep learning and aggregation network based face surveillance system, tested by realistic scenarios (Unpublished master thesis advised by professor Being-Fei Wu). National Chiao Tung University, Hsinchu, Taiwan (2018)
Yang, J., Ren, P., Chen, D., Wen, F., Li, H., Hua, G.: Neural aggregation network for video face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CoRR (2016)
Zhang, K., Zhang, Z., Li, Z., Qiao, Y.: Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process. Lett. 23(10), 1499–1503 (2016)
Lucey, P., Cohn, J.F., Kanade, T., Saragih, J., Ambadar, Z., Matthews, I.: The extended Cohn-Kanade dataset (CK +): a complete facial expression dataset for action unit and emotion-specified expression. In: 3rd IEEE Workshop on CVPR for Human Communicative Behavior Analysis (2010)
Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D.H.J., Hawk, S.T., van Knippenberg, A.: Presentation and validation of the Radboud faces database. Cogn. Emot. 24(8), 1377–1388 (2010)
Van der Schalk, J., Hawk, S.T., Fischer, A.H., Doosje, B.J.: Moving faces, looking places: the Amsterdam Dynamic Facial Expressions Set (ADFES). Emotion 11, 907–920 (2011)
Facial action coding system. https://www.paulekman.com/facial-action-coding-system/. Accessed 2019
Zhang, X., et al.: BP4D-spontaneous: a high-resolution spontaneous 3D dynamic facial expression database. Image Vis. Comput. 32, 692–706 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lin, S.S.J., Chen, W., Lin, CH., Wu, BF. (2019). Building a Chinese Facial Expression Database for Automatically Detecting Academic Emotions to Support Instruction in Blended and Digital Learning Environments. In: Rønningsbakk, L., Wu, TT., Sandnes, F., Huang, YM. (eds) Innovative Technologies and Learning. ICITL 2019. Lecture Notes in Computer Science(), vol 11937. Springer, Cham. https://doi.org/10.1007/978-3-030-35343-8_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-35343-8_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35342-1
Online ISBN: 978-3-030-35343-8
eBook Packages: Computer ScienceComputer Science (R0)