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Cognitive Characteristics Based Autonomous Development of Clothing Style

  • Jiyun Li
  • Xiaodong Zhong
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 849)

Abstract

Due to the subjective characteristics and rapid change of fashion style, it is relatively hard to predefine the style feature in style classification systems. In this paper we present a cognitive characteristics based clothing style autonomous development model. By the addition of special domain related information to the classic itti visual attention model, we achieve the multi-object attention model of the clothing style. And based on this we implemented the autonomous development of clothing style recognition by Multi-Layer In-place Learning Network (MILN in short). Experiments prove the feasibility and effectiveness of our model.

Keywords

Clothing style Multi-object MILN LCA Autonomous development Visual attention 

References

  1. 1.
    Huang, Q., Sun, S.: The research progress for the calculation in product styles. J. Comput. Aided Des. Comput. Graph. 18, 1629–1636 (2006)Google Scholar
  2. 2.
    Chan, C.-S.: Can style be measured. Des. Stud. 21, 227–291 (2000)CrossRefGoogle Scholar
  3. 3.
    Feng, L., Liu, X.: First exploration of the ways to quantify clothing styles. J. Donghua Univ. (Nat. Sci.) 30(1), 57–61 (2004)Google Scholar
  4. 4.
    Weng, J., Luwang, T., Lu, H.: A multilayer in-place learning network for development of general invariances. Int. J. Humanoid Rob. 4(2), 281–320 (2007)CrossRefGoogle Scholar
  5. 5.
    Robert, J., Laurent, I.: Beyond Bottom-up: incorporating task-dependent influences into a computational model of spatial attention. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)Google Scholar
  6. 6.
    Huang, Q., Sun, S.: The recognition method for product styles based on matching features. China Mech. Eng. 14, 1836–1838 (2003)Google Scholar
  7. 7.
    Weng, J., Luciw, M.: Dually optimal neuronal layers: lobe component analysis. IEEE Trans. Auton. Ment. Dev. 1(1), 68–85 (2009)CrossRefGoogle Scholar
  8. 8.
    M, W., M, T.: Cognitive Psychology: A Student’s Handbook, 6th ed., Psychology Press (2010)Google Scholar
  9. 9.
    Chen, J.: Researches for the mode of style operation which is used to design product style. Ind. Des. 28, 111–115 (2000)Google Scholar
  10. 10.
    Cheng, G., Li, J.: Research on clothing style preference model based on interactive genetic algorithm. Comput. Appl. Softw. 28(2), 229–231 (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Computer Sciences and TechnologyDonghua UniversityShanghaiChina

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