Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-10T20:07:06.722Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic fuzzy modeling of user perception of three-dimensional shapes

Published online by Cambridge University Press:  07 February 2011

Sofiane Achiche  and
Saeema Ahmed-Kristensen
Sofiane Achiche
Affiliation:
Management Engineering Department, Engineering Design and Product Development Section, Technical University of Denmark, Lyngby, Denmark
Saeema Ahmed-Kristensen
Affiliation:
Management Engineering Department, Engineering Design and Product Development Section, Technical University of Denmark, Lyngby, Denmark
Get access Rights & Permissions [Opens in a new window]

Abstract

Defining the aesthetic and emotional value of a product is an important consideration for its design. Furthermore, if several designers are faced with the task of creating an object that describes a certain emotion/perception (aggressive, soft, heavy, etc.), each is most likely to interpret the emotion/perception with different shapes composed of a set of different geometric features. The authors propose an automatic approach to formalize the relationships between geometric information of three-dimensional objects and the intended emotional content using fuzzy logic. In addition, the automatically generated fuzzy knowledge base was compared to the user's perceptions and to the manually constructed fuzzy knowledge base. The initial findings indicate that the approach is valid to formalize geometric information with perceptions and validate the author's manually developed fuzzy models.

Keywords

AestheticsAutomatic OptimizationDesign CharacteristicsEmotional DesignFuzzy LogicGenetic Algorithms
Type
Articles
Information
AI EDAM , Volume 25 , Issue 1 , February 2011 , pp. 93 - 107
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Achiche, S., & Ahmed, S. (2008). Mapping shape geometry and emotions using fuzzy logic. Proc. 2008 ASME IDETC/CIE, Paper No. DETC2008-49290.CrossRefGoogle Scholar
Achiche, S., Balazinski, M., & Baron, L. (2004). Multi-combinative strategy to avoid premature convergence in genetically-generated fuzzy knowledge bases. Journal of Theoretical and Applied Mechanics 42(3), 417–444.Google Scholar
Achiche, S., Baron, L., & Balazinski, M. (2003). Real/binary like coded genetic algorithm to automatically generate fuzzy knowledge bases. Proc. IEEE 4th Int. Conf. Control and Automation, pp. 799–803, Montreal.Google Scholar
Ahmed, S., & Boelskifte, P. (2006). Investigation of designers intentions and users' perception of product character. Proc. Nordesign, pp. 372–381, Reykjavik, Iceland.Google Scholar
Balazinski, M., Achiche, S., & Baron, L. (2000). Influences of optimization criteria on genetically generated fuzzy knowledge bases. Proc. Int. Conf. Advanced Manufacturing Technology, pp. 159–164.Google Scholar
Baron, L., Achiche, S., & Balazinski, M. (2001). A genetic-based learning process for fuzzy decision support systems. International Journal of Approximate Reasoning 28(2–3), 125–148.CrossRefGoogle Scholar
Bloch, P.H. (1995). Seeking the ideal form: product design and the consumer response. Journal of Marketing 59, 16–29.CrossRefGoogle Scholar
Bouchard, C., Christofol, H., Roussel, B., Auvray, L., & Aoussat, A. (1999). Identification and integration of product design trends. Proc. Int. Conf. Engineering Design, ICED 99, pp. 1147–1150.Google Scholar
Bruce, M., & Whitehead, M. (1988). Design into the picture: the role of product design in consumer purchase behaviour. Journal of Market Research Society 30(2), 147–162.Google Scholar
Chuang, M.C., Chang, C.C., & Hsu, S.H. (2001). Perceptual factors underlying user preferences toward product form of mobile phones. International Journal of Industrial Ergonomics 27, 247–258.CrossRefGoogle Scholar
Company, P., Vergara, M., & Mondragón, S. (2004). Contributions to product semantics taxonomy. Proc. 8th Congreso Int. Ingeniería de Proyectos, Bilba, Spain.Google Scholar
Cordòn, O., Herrera, F., & Villar, P. (2000). Analysis and guidelines to obtain a good uniform fuzzy partition granularity for fuzzy-rule based systems using simulated annealing. International Journal of Approximate Reasoning 25(3), 187–215.CrossRefGoogle Scholar
Diyar Akay, D., & Kurt, M. (2009). A neuro-fuzzy based approach to affective design. International Journal of Advanced Manufacturing Technology 40(5–6), 425–437.CrossRefGoogle Scholar
Dore, R., Pailhes, J., Fischer, X., & Nadeau, J.-P. (2007). Identification of sensory variables towards the integration of user requirements into preliminary design. International Journal of Industrial Ergonomics 37(1), 1–11.CrossRefGoogle Scholar
Duda, R.O., Hart, P.E., & Stork, D.G. (2001). Pattern Classification, 2nd ed. New York: Wiley.Google Scholar
Giannini, F., Monti, M., & Podehl, G. (2006). Aesthetic-driven tools for industrial design. Journal of Engineering Design 17(3), 193–215.CrossRefGoogle Scholar
Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison–Wesley.Google Scholar
Goldman, A.H. (1995). Aesthetic Value. Denver, CO: Westview Press.Google Scholar
Hsiao, S.W., & Chen, C.H. (1997). A semantic and shape grammar based approach for product design. Design Studies 18, 275–296.CrossRefGoogle Scholar
Hsiao, S.W., & Wang, H.P. (1998). Applying the semantic transformation method to product design. Design Studies 19(3), 309–330.CrossRefGoogle Scholar
Hsiao, S.W., & Tsai, H.C. (2005). Applying a hybrid approach based on fuzzy neural network and genetic algorithm to product form design. International Journal of Industrial Ergonomics 35(5), 411–428.CrossRefGoogle Scholar
Jianning, S., & Fenqiang, L. (2007). Research of product styling design method based on neural network. Proc. 3rd Int. Conf. Natural Computation, pp. 499–504.Google Scholar
Knight, T. (1999). Shape grammars in education and practice: history and prospects. International Journal of Design Computing 2. Accessed at http://www.mit.edu/~tknight/IJDC/Google Scholar
Lai, H.-H., Lin, Y.-C., & Yeh, C.-H. (2005). Form design of product image using grey relational analysis and neural network models. Computers and Operations Research 32, 2689–2711.CrossRefGoogle Scholar
Lai, H.H., Lin, Y.C., Yeh, C.H., & Wei, C.H. (2006). User-oriented design for the optimal combination on product design. International Journal Production Economics 100(2), 253–267.CrossRefGoogle Scholar
Lawson, B. (1983). How Designers Think. Westfield, NJ: Eastview Editions.Google Scholar
Lebbon, C., & McDonagh-Philp, D.C. (2000). Exploring the emotional relationship between users and products. Proc. Designing for the 21st Century II: Int. Conf. Universal Design. Accessed at http://www.adaptenv.org/21century/proceedings4.aspGoogle Scholar
Lenau, T., & Boelskifte, P. (2004). Soft and hard product attributes in design. Working paper F28, pp. 6–13, University of Art and Design, Helsinki.Google Scholar
Lenau, T., & Boelskifte, P. (2005). Verbal communication of semantic content in products. Proc. Nordesign “In The Making” Conf.CrossRefGoogle Scholar
Lin, Y.C., Lai, H.H., & Yeh, C.H. (2007). Consumer-oriented product form design based on fuzzy logic: a case study of mobile phones. International Journal of Industrial Ergonomics 37, 531–543.CrossRefGoogle Scholar
Lyons, A. (2001). Gestalt approaches to the virtual gesamtkunstwerk. Accessed at http://www.tstex.com on April 10, 2010.Google Scholar
Michalewicz, Z. (1992). Genetic Algorithms + Data Structure = Evolution Programs. New York: Springer.CrossRefGoogle Scholar
Mohais, A., Nikov, A., Sahai, A., & Nesil, S. (2007). Swarm-optimization-based affective product design illustrated by a pen case-study. Proc. 23rd World Academy of Science, Engineering and Technology Conf., pp. 240–245.Google Scholar
Norikazu, I., Hiroshi, M., Yukihiro, K., Tomomi, T., & Daisuk, Y. (2001). Building exterior design system by hierarchical combination fuzzy model. Proc. 5th Conf. North American Fuzzy Information Processing Society, NAFIPS, pp. 2573–2578.Google Scholar
Norman, D., & Olaf, H. (1963). An experimental application of the Delphi method to the use of experts. Management Science 9(3), 458–467.Google Scholar
Norman, D.A. (2004). Emotional Design: Why We Love (or Hate) Everyday Things. New York: Basic Books.Google Scholar
Ortony, A., & Turner, T.J. (1990). What's basic about basic emotions? Psychological Review 97(3), 315–331.CrossRefGoogle ScholarPubMed
Park, J., & Han, S.H. (2004). A fuzzy rule-based approach to modeling affective user satisfaction towards office chair design. International Journal of Industrial Ergonomics 34, 31–47.CrossRefGoogle Scholar
Pham, B. (1999). Design for aesthetics: interactions of design variables and aesthetic properties. Proc. SPIE IS&T/SPIE 11th Annual Symp., Electronic Imaging ‘99, pp. 364–371.Google Scholar
Pupo, R., Pinheiro, E., Mendes, G., Kowaltowski, D., & Celani, G. (2007). A design teaching method using shape grammars. Proc. 7th Int. Conf. Graphics Engineering for Arts and Design, pp. 1–10.Google Scholar
Schamber, L. (1986). A content-driven approach to visual literacy: Gestalt rediscovered. Proc. 69th Annual Meeting of the Association for Education in Journalism and Mass Communication.Google Scholar
Shieh, D.M., & Yang, C.C. (2008). Multiclass SVM-RFE for product form feature selection. Expert Systems With Applications 35, 531–541.CrossRefGoogle Scholar
Smyth, S.N., & Wallace, D.R. (2000). Towards the synthesis of aesthetic product form. Proc. 2000 ASME Design Engineering Technical Conf. Computers and Information in Engineering Conf., DETC’00, Paper No. DETC2000/DTM-14554, Baltimore, MD.CrossRefGoogle Scholar
Strasser, S., London, L., & Kortenbout, E. (2005). Developing a competence framework and evaluation tool for primary care nursing in South Africa. Education for Health 18(2), 133–144.CrossRefGoogle ScholarPubMed
Tsai, H.C., Hsiao, H.W., & Hung, F.K. (2006). An image evaluation approach for parameter-based product form and colour design. Computer-Aided Design 38, 157–171.CrossRefGoogle Scholar
Tsutsumi, K., & Sasaki, K. (2008). Study on shape creation of building's roof by evaluating aesthetic sensibility. Mathematics and Computers in Simulation 77, 487–498.CrossRefGoogle Scholar
Van Bremen, E.J.J., Knoop, W.G., Horvath, I., & Vergeest, J.S.M. (1998). Developing a methodology for design for aesthetics based on analogy of communication. Proc. 1998 ASME Design Engineering Technical Conf., Paper No. DET98/DAC-5614.Google Scholar
Wallace, D.R., & Jakiela, M.J. (1993). Automated product concept design: unifying aesthetic and engineering. IEEE Computer Graphics and Applications 13(4), 66–75.CrossRefGoogle Scholar
Yen, J., & Langari, R. (1998). Fuzzy Logic: Intelligence, Control, and Information. Englewood Cliffs, NJ: Prentice–Hall.Google Scholar
Zadeh, L.A. (1965). Fuzzy sets. Information Control 8, 339–353.CrossRefGoogle Scholar