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International Symposium on Visual Computing

ISVC 2012: Advances in Visual Computing pp 210–219Cite as

Large Scale Sketch Based Image Retrieval Using Patch Hashing

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7431))

Abstract

This paper introduces a hashing based framework that facilitates sketch based image retrieval in large image databases. Instead of exporting a single visual descriptor for every image, an overlapping spatial grid is utilised to generate a pool of patches. We rank similarities between a hand drawn sketch and the natural images in a database through a voting process where near duplicate in terms of shape and structure patches arbitrate for the result. Patch similarity is efficiently estimated with a hashing algorithm. A reverse index structure built on the hashing keys ensures the scalability of our scheme and at the same time allows for real time reranking on query updates. Experiments in a publicly available benchmark dataset demonstrate the superiority of our approach.

This work is partially supported by EU project CUBRIK under grant agreement FP7 287704.

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References

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

    Article  Google Scholar 

  2. Eitz, M., Kristian Hildebrand, T.B., Alexa, M.: A descriptor for large scale image retrieval based on sketched feature lines. In: Eurographics Symposium on Sketch-Based Interfaces and Modeling, pp. 29–38 (2009)

    Google Scholar 

  3. Cole, F., Golovinskiy, A., Limpaecher, A., Barros, H.S., Finkelstein, A., Funkhouser, T., Rusinkiewicz, S.: Where do people draw lines? Communications of the ACM 55, 107–115 (2012)

    Article  Google Scholar 

  4. Cole, F., Sanik, K., DeCarlo, D., Finkelstein, A., Funkhouser, T., Rusinkiewicz, S., Singh, M.: How well do line drawings depict shape? ACM Transactions on Graphics (Proc. SIGGRAPH) 28 (2009)

    Google Scholar 

  5. Eitz, M., Hildebrand, K., Boubekeur, T., Alexa, M.: Sketch-based image retrieval: Benchmark and bag-of-features descriptors. IEEE Transactions on Visualization and Computer Graphics 17, 1624–1636 (2011)

    Article  Google Scholar 

  6. Broder, A.Z., Charikar, M., Frieze, A.M., Mitzenmacher, M.: Min-wise independent permutations. Journal of Computer and System Sciences 60, 327–336 (1998)

    MathSciNet  Google Scholar 

  7. Chum, O., Philbin, J., Zisserman, A.: Near duplicate image detection: min-hash and tf-idf weighting. In: Proceedings of the British Machine Vision Conference (2008)

    Google Scholar 

  8. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 1, pp. 886–893 (2005)

    Google Scholar 

  9. Hirata, K., Kato, T.: Query by Visual Example. In: Pirotte, A., Delobel, C., Gottlob, G. (eds.) EDBT 1992. LNCS, vol. 580, pp. 56–71. Springer, Heidelberg (1992)

    Chapter  Google Scholar 

  10. Lopresti, D., Tomkins, A.: Computing in the ink domain. In: Yuichiro Anzai, K.O., Mori, H. (eds.) Symbiosis of Human and Artifact - Future Computing and Design for Human-Computer Interaction. Proceedings of the Sixth International Conference on Human-Computer Interaction (HCI International 1995). Advances in Human Factors/Ergonomics, vol. 20, pp. 543–548. Elsevier (1995)

    Google Scholar 

  11. Liang, S., Sun, Z., Li, B.: Sketch retrieval based on spatial relations. In: Proc. Int. Computer Graphics, Imaging and Vision: New Trends Conf., pp. 24–29 (2005)

    Google Scholar 

  12. Del Bimbo, A., Pala, P.: Visual image retrieval by elastic matching of user sketches. IEEE Transactions on Pattern Analysis and Machine Intelligence 19, 121–132 (1997)

    Article  Google Scholar 

  13. Matusiak, S., Daoudi, M., Blu, T., Avaro, O.: Sketch-Based Images Database Retrieval. In: Jajodia, S., Özsu, M.T., Dogac, A. (eds.) MIS 1998. LNCS, vol. 1508, pp. 185–191. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  14. Chalechale, A., Naghdy, G., Mertins, A.: Sketch-based image matching using angular partitioning. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 35, 28–41 (2005)

    Article  Google Scholar 

  15. Eitz, M., Hildebrand, K., Boubekeur, T., Alexa, M.: A descriptor for large scale image retrieval based on sketched feature lines. In: Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling, SBIM 2009, pp. 29–36. ACM, New York (2009)

    Chapter  Google Scholar 

  16. Sivic, J., Zisserman, A.: Video Google. In: Proceedings of the International Conference on Computer Vision, vol. 2, pp. 1470–1477 (2003)

    Google Scholar 

  17. Hu, R., Barnard, M., Collomosse, J.: Gradient field descriptor for sketch based retrieval and localization. In: Proc. 17th IEEE Int. Conf. Image Processing, ICIP, pp. 1025–1028 (2010)

    Google Scholar 

  18. Hu, R., Wang, T., Collomosse, J.: A bag-of-regions approach to sketch-based image retrieval. In: 2011 18th IEEE International Conference on Image Processing, ICIP, pp. 3661–3664 (2011)

    Google Scholar 

  19. Cao, Y., Wang, C., Zhang, L., Zhang, L.: Edgel index for large-scale sketch-based image search. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 761–768 (2011)

    Google Scholar 

  20. Lee, Y.J., Zitnick, C.L., Cohen, M.F.: Shadowdraw: real-time user guidance for freehand drawing. ACM Trans. Graph. 30, 27 (2011)

    Article  Google Scholar 

  21. Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing, STOC 1998, pp. 604–613. ACM, New York (1998)

    Chapter  Google Scholar 

  22. Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679–698 (1986)

    Article  Google Scholar 

  23. Martin, D., Fowlkes, C., Malik, J.: Learning to detect natural image boundaries using local brightness, color, and texture cues. IEEE Transactions on Pattern Analysis and Machine Intelligence 26, 530–549 (2004)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. School of Electronic Engineering and Computer Science, Queen Mary University of London, Mile End Campus, UK, E1 4NS

    Konstantinos Bozas & Ebroul Izquierdo

Authors
  1. Konstantinos Bozas
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  2. Ebroul Izquierdo
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, 89512, Reno, NV, USA

    Darko Koracin

  5. Department of Computer Science, University of California at Irvine, 92697-3435, Irvine, CA

    Charless Fowlkes

  6. Eastman Kodak Company, 14650-2102, Rochester, NY, USA

    Sen Wang

  7. Department of Computer Science and Engineering, University of Colorado at Denver, 80217, Denver, CO, USA

    Min-Hyung Choi

  8. VRVis Zentrum für Virtual Reality and Visualisierung, 1220, Vienna, Austria

    Stephan Mantler

  9. California Institute for Telecommunications and Information Technology, University of California, 92093, San Diego, La Jolla, CA, USA

    Jürgen Schulze

  10. KAUST Visualizatioin Core Lab., 23955-6900, Thurwal, Saudi Arabia

    Daniel Acevedo

  11. Stony Brook University, 11794-4400, NY, USA

    Klaus Mueller

  12. Argonne National Laboratory, 60439, IL, USA

    Michael Papka

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© 2012 Springer-Verlag Berlin Heidelberg

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Bozas, K., Izquierdo, E. (2012). Large Scale Sketch Based Image Retrieval Using Patch Hashing. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33179-4_21

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  • DOI: https://doi.org/10.1007/978-3-642-33179-4_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33178-7

  • Online ISBN: 978-3-642-33179-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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