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EasySketchDesign: Product Sketch Design Assisted with Interactive Sketch Retrieval

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Artificial Intelligence in HCI (HCII 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12217))

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Abstract

We present EasySketchDesign, a sketch interface that integrates the sketch retrieval technique to search pictures related to current design form the image library quickly and exactly. The sketch drawn by the designer and the referential product data set are first transformed into a clear outline by means of edge detection, image dilation, etc. Then, the improved Recursive Cortical Network (RCN) is used to select the existing products similar to the sketch. Through such a design mode, the designer can be inspired by other people’s work. Besides, they can know whether their work has the risk of being the same as the existing product to guarantee innovation. The evaluation study shows this system is easy to use and effective in transcending the creative potential of traditional sketching in Product conceptual design.

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References

  1. Eitz, M., Hildebrand, K., Boubekeur, T., Alexa, M.: Sketch-Based image retrieval: benchmark and bag-of-features descriptors. IEEE Trans. Vis. Comput. Graph. 17(11), 1624–1636 (2010)

    Article  Google Scholar 

  2. Paper, C., Cheng, M., Huang, X., Hu, S.: Global contrast based salient region detection. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 569–582 (2011). https://doi.org/10.1109/CVPR.2011.5995344

    Article  Google Scholar 

  3. Sousa, P., Fonseca, M.J.: Sketch-based retrieval of drawings using spatial proximity. J. Vis. Lang. Comput. 21(2), 69–80 (2010)

    Article  Google Scholar 

  4. Del Bimbo, A., Pala, P., Santini, S.: Visual image retrieval by elastic deformation of object sketches. In: Proceedings of 1994 IEEE Symposium on Visual Languages, pp. 216–223. IEEE (1994)

    Google Scholar 

  5. Chalechale, A., Naghdy, G., Mertins, A.: Sketch-based image matching using angular partitioning. IEEE Trans. Syst. Man Cybern.-Part A: Syst. Hum. 35(1), 28–41 (2004)

    Article  Google Scholar 

  6. Yang, Y., Hospedales, T.M.: Deep Neural Networks for Sketch Recognition (2015)

    Google Scholar 

  7. Qi, Y., Zhang, H.: Sketch-Based Image Retrieval Via SIAMESE Convolutional Neural Network Yi-Zhe Song School of Information and Communication Engineering, BUPT, Beijing, China School of EECS, Queen Mary University of London, UK

    Google Scholar 

  8. Bui, T., Collomosse, J., Ribeiro, L., Ponti, M., Paulo, S.: Generalisation and Sharing in Triplet Convnets for Sketch based Visual Search (2016)

    Google Scholar 

  9. Wang, J., et al.: Learning fine-grained image similarity with deep ranking. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1386–1393 (2014)

    Google Scholar 

  10. George, D., George, D., Lehrach, W., et al.: A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs. Science 2612, 1–19 (2017)

    Google Scholar 

  11. Craft, E., et al.: A neural model of figure – ground organization. J. Neurophysiol. 97(6), 4310–4326 (2007)

    Article  Google Scholar 

  12. Lamme, V.A.F., Rodriguez-rodriguez, V.: Separate processing dynamics for texture elements. Boundaries Surf. Primary Visual Cortex Macaque Monkey 1, 406–413 (1999)

    Google Scholar 

  13. Deyoe, E.A., Van Essen, D.C.: Concurrent processing streams in monkey visual cortex. Trends Neurosci. 11, 219–226 (1988)

    Article  Google Scholar 

  14. Le, R., Heess, N.: Learning a generative model of images by factoring appearance and shape. Neural Comput. 23, 593–650 (2010)

    MathSciNet  MATH  Google Scholar 

  15. Pearl, J.: Probabilistic reasoning in intelligent systems : networks of plausible inference (1988)

    Google Scholar 

  16. Datta, R., Joshi, D., Li, J.I.A., Wang, J.Z.: Image retrieval: ideas influences, and trends of the new age. ACM Comput. Surv. (Csur) 40, 1–60 (2008)

    Article  Google Scholar 

  17. Sun, X.: Indexing Billions of Images for Sketch-based Retrieval, pp. 233–242 (2013)

    Google Scholar 

  18. Hu, R., Collomosse, J.: A performance evaluation of gradient field hog descriptor for sketch based image retrieval. Comput. Vis. and Image Understand. 117(7), 790–806 (2013)

    Article  Google Scholar 

  19. The completion time of each participant (s)

    Google Scholar 

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Correspondence to Yukun Hu .

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Appendix A

Appendix A

Sketching with EasySketchDesign

Purely sketching

P2

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P1

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Hu, Y., Yu, S., Chu, J., Yang, Y., Chen, C., Cheng, F. (2020). EasySketchDesign: Product Sketch Design Assisted with Interactive Sketch Retrieval. In: Degen, H., Reinerman-Jones, L. (eds) Artificial Intelligence in HCI. HCII 2020. Lecture Notes in Computer Science(), vol 12217. Springer, Cham. https://doi.org/10.1007/978-3-030-50334-5_21

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  • DOI: https://doi.org/10.1007/978-3-030-50334-5_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-50333-8

  • Online ISBN: 978-3-030-50334-5

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