Abstract
Since the empathic processes are essential to the aesthetic experience, the empathy-enabling technology for behavioral sensing is gaining its popularity to support the study of anonymized viewers’ cognition in art appreciation. Because such behavior is highly dynamic and divergent among viewers, it is a challenge to observe the multiple dynamic features from the streaming data. In this study, we propose a vision sensor network (VSN) to support the visual interpretation of viewers’ appreciation on visual arts. It firstly annotates the features in the captured frames based on CloudAPI (here the Google Cloud Vision API is used), and secondly the query on nested documents in MongoDB provides universal access to the annotated features. Comparing with the traditional approaches with subjective evidence, such as the questionnaire or social listening methods, the proposed VSN can interpret the visible behavior of viewers in real-time. In addition, it also has less selective bias because of more objective evidence being captured.
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
Ek, R., Larsen, J., Hornskov, S.B., Mansfeldt, O.K.: A dynamic framework of tourist experiences: space-time and performances in the experience economy. Scand. J. Hosp. Tour. 8(2), 122–140 (2008)
Larsen, S.: Aspects of a psychology of the tourist experience. Scand. J. Hosp. Tour. 7(1), 7–18 (2007)
Montelongo, S.: Comparing image tagging services: Google Vision, Microsoft Cognitive Services, Amazon Rekognition and Clarifai. https://www.reaktor.com/blog/the-rise-of-empathy-enabling-technology/. Accessed 15 May 2018
Sheng, C.-W., Chen, M.-C.: Tourist experience expectations: questionnaire development and text narrative analysis. Int. J. Cult. Touri. Hosp. Res. 7(1), 93–104 (2013)
Liu, Y., et al.: Social sensing: a new approach to understanding our socioeconomic environments. Ann. Assoc. Am. Geogr. 105(3), 512–530 (2015)
Gernot, G., Pelowski, M., Leder, H.: Empathy, einfühlung, and aesthetic experience: the effect of emotion contagion on appreciation of representational and abstract art using fEMG and SCR. Cogn. Process. 19(2), 147–165 (2018)
Mokhtari, G., Bashi, N., Zhang, Q., Nourbakhsh, G.: Non-wearable human identification sensors for smart home environment: a review. Sens. Rev. 38(3), 391–404 (2018)
Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Comput. Surv. (Csur) 40(2), 5 (2008)
Bartra, O.: JavaScript Image Comparison. https://github.com/obartra/ssim. Accessed 15 Aug 2018
Huang, L.: Water Color Paintings of Mr. Cat Petter and His Cat Friends. http://cms.huangluyi.com/cn/?p=240. Accessed 05 Aug 2018
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
Wu, Y., Huang, L., Wei, Z., Cheng, Z. (2019). A Vision Sensor Network to Study Viewers’ Visible Behavior of Art Appreciation. In: Kojima, K., Sakamoto, M., Mineshima, K., Satoh, K. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2018. Lecture Notes in Computer Science(), vol 11717. Springer, Cham. https://doi.org/10.1007/978-3-030-31605-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-31605-1_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-31604-4
Online ISBN: 978-3-030-31605-1
eBook Packages: Computer ScienceComputer Science (R0)