Abstract
Focusing on the problem of high-level semantic ambiguity in the initial concept. This paper aims to fill the gap between abstract design concepts and specific design solutions. In this paper, the high-level semantic visual representation process is divided into two parts: image representation and meaning acquisition. The mood board tool with three levels of scene layer, feature layer, and form layer is proposed. Two symbiotic clues existed in the mood board tool: visual cue and meaning cue, corresponding to image representation and meaning acquisition. The effectiveness and feasibility are verified through the case application of automotive styling design. The process of image expression and meaning acquisition embodies the unity of content and form in the process of high-level semantic visual representation. The mood board tool for high-level semantic visual representation provides validity and feasibility in bridging the gap between abstract design inputs and specific design outcomes.
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References
Schifferstein, H.N.J., Hekkert, P., (eds.): Product Experience. Elsevier (2011)
Ishihara, S., et al.: Affective meaning: the Kansei engineering approach. In: Product Experience, pp. 477–496. Elsevier (2008)
Kim, J.: Modeling cognitive and affective processes of designers in the early stages of design: mental categorization of information processing. Diss. Arts et Métiers ParisTech (2011)
Lucero, A.: Framing, aligning, paradoxing, abstracting, and directing: how design mood boards work. In: Proceedings of the Designing Interactive Systems Conference (2012)
Bouchard, C., Aoussat, A., Duchamp, R.: Role of sketching in conceptual design of car styling. J. Des. Res. 5(1), 116–148 (2006)
Sachse, P., Furtner, M.: Embodied knowledge in design. In: After Cognitivism, pp. 163–179. Springer, Dordrecht (2009)
Rieuf, V., et al.: Emotional activity in early immersive design: Sketches and moodboards in virtual reality. Des. Stud. 48, 43–75 (2017)
Zhao, J.-H., Tan, H., Tan, Z.: Car Styling: Theory, Research and Application, p. 47. Beijing Institute of Technology Press, Beijing (2011)
Wölfel, C., Krzywinski, J., Drechsel, F.: Knowing, reasoning and visualizing in industrial design. Knowl. Eng. Rev. 28(3), 287–302 (2013)
Renaud, K., Van Biljon, J.: A framework to maximise the communicative power of knowledge visualisations. In: Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019, pp. 1–10 (2019)
Kim, E., Kim, K.: Cognitive styles in design problem solving: Insights from network-based cognitive maps. Des. Stud. 40, 1–38 (2015)
Sachse, P.: Idea materialis: Entwurfsdenken und Darstellungshandeln: über die allmähliche Verfertigung der Gedanken beim Skizzieren und Modellieren. Logos-Verlag (2002)
Garner, S., McDonagh-Philp, D.: Problem interpretation and resolution via visual stimuli: the use of ‘mood boards’ in design education. J. Art Des. Educ. 20(1), 57–64 (2001)
Freeman, C., Marcketti, S., Karpova, E.: Creativity of images: using digital consensualassessment to evaluate mood boards. Fashion Text. 4(17), 1 (2017)
McDonagh, D., Storer, I.: Mood boards as a design catalyst and resource: researching an under-researched area. Des. J. 7(3), 16–31 (2004)
Zabotto, C.N., et al.: Automatic digital mood boards to connect users and designers with Kansei engineering. Int. J. Ind. Ergon. 74, 102829 (2019)
Brevi, F., Manuela, C., Flora, G.: Creating moodboards with digital tools: a new educational approach. In: International Conference on Education and New Developments 2019, vol. 1. InScience Press (2019)
Celi, M.: Design, metadesign and the importance of vision. Strateg. Des. Res. J. 5(2), 84–90 (2012)
Pirolli, P., Card, S.: The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. In: Proceedings of International Conference on Intelligence Analysis, vol. 5 (2005)
Teevan, J., et al.: The perfect search engine is not enough: a study of orienteering behavior in directed search. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2004)
Mougenot, C., et al.: Inspiration, images and design: an investigation of designers’ information gathering strategies. J. Des. Res. 7(4), 331–351 (2008)
Koch, J., et al.: SemanticCollage: enriching digital mood board design with semantic labels. In: Proceedings of the 2020 ACM Designing Interactive Systems Conference (2020)
Casakin, H., Goldschmidt, G.: Expertise and the use of visual analogy: implications for design education. Des. Stud. 20(2), 153–175 (1999)
Foucault Welles, B., Meirelles, I.: Visualizing computational social science: the multiple lives of a complex image. Sci. Commun. 37(1), 34–58 (2015)
Kallick-Wakker, I.: Science icons: the visualization of scientific truths. Leonardo 27(4), 309–315 (1994)
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We would like to thank the National Social Science Foundation of China (20BG103) for providing this research with financial support.
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Li, Tt., Zhao, Dh. (2021). Mood Board Tool on High-level Semantics Visual Representation to Favor Creative Design. In: Rebelo, F. (eds) Advances in Ergonomics in Design. AHFE 2021. Lecture Notes in Networks and Systems, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-030-79760-7_49
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