Skip to main content
SpringerLink
Log in

Celebrity Face Image Retrieval Using Multiple Features

  • Conference paper
Neural Information Processing (ICONIP 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8836))

Included in the following conference series:

  • 4419 Accesses

Abstract

Large scale face image retrieval is a hot topic in the field of internet retrieval. There exist a number of interesting applications of face image processing, such as hair-style design. In this paper, we propose a content-based face image retrieval system aiming at finding similar photos of celebrities to a user input image using a novel fusion of features and evaluation of results. After image preprocessing such as cropping facial parts and feature extraction with some exoteric methods, an algorithm we propose remolds the traditional features based on their statistic characteristics. The remolded features are then fused to a novel image representation to retrieve face images more effectively. A large number of experiments based on the dataset collected on the Internet demonstrate the good performance of our method in Mean Average Precision (MAP).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Datta, R., Joshi, D., Li, J., Wang, J.Z.: Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys (CSUR) 40(2), 5 (2008)

    Article  Google Scholar 

  2. Lee, H., Chung, Y., Kim, J., Park, D.: Face image retrieval using sparse representation classifier with gabor-LBP histogram. In: Chung, Y., Yung, M. (eds.) WISA 2010. LNCS, vol. 6513, pp. 273–280. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  3. Viola, P., Jones, M.J.: Robust real-time face detection. International Journal of Computer Vision 57(2), 137–154 (2004)

    Article  Google Scholar 

  4. Shih, P., Liu, C.: Comparative assessment of content-based face image retrieval in different color spaces. International Journal of Pattern Recognition and Artificial Intelligence 19(07), 873–893 (2005)

    Article  Google Scholar 

  5. Smith, A.R.: Color gamut transform pairs. ACM Siggraph Computer Graphics 12(3), 12–19 (1978)

    Article  Google Scholar 

  6. 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. IEEE (2005)

    Google Scholar 

  7. Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)

    Article  Google Scholar 

  8. Ahonen, T., Hadid, A., Pietikäinen, M.: Face recognition with local binary patterns. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 469–481. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  9. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(12), 2037–2041 (2006)

    Article  Google Scholar 

  10. Liu, S., Song, Z., Liu, G., Xu, C., Lu, H., Yan, S.: Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3330–3337. IEEE (2012)

    Google Scholar 

  11. Wu, Z., Ke, Q., Sun, J., Shum, H.-Y.: Scalable face image retrieval with identity-based quantization and multireference reranking. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(10), 1991–2001 (2011)

    Article  Google Scholar 

  12. Chen, B., Chen, Y., Kuo, Y., Hsu, W.: Scalable face image retrieval using attribute-enhanced sparse codewords, 1 (2012)

    Google Scholar 

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

    Google Scholar 

  14. Smith, B.M., Zhu, S., Zhang, L.: Face image retrieval by shape manipulation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 769–776. IEEE (2011)

    Google Scholar 

  15. Zhou, R., Chen, L., Zhang, L.: Sketch-based image retrieval on a large scale database. In: Proceedings of the 20th ACM International Conference on Multimedia, pp. 973–976. ACM (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Dept. of Computer Science and Engineering, Shanghai Jiao Tong University, China

    Jie Jin & Liqing Zhang

Authors
  1. Jie Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Faculty of Computer Science and Information Technology Building, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Chu Kiong Loo

  2. Department of Electronics and Communication Engineering, College of Engineering, Jalan IKRAM-UNITEN, Universiti Tenaga Nasional, 43009, Kajang, Selangor, Malaysia

    Keem Siah Yap

  3. School of Engineering and Information Technology, Murdoch University, 6150, South St, Murdoch, Western Australia, Australia

    Kok Wai Wong

  4. Department of Electrical and Electronics Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, 120-749, Seoul, South Korea

    Andrew Teoh Beng Jin

  5. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Ren’ai Road 111, SIP 215123, Suzhou, Jiangsu Province, China

    Kaizhu Huang

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Jin, J., Zhang, L. (2014). Celebrity Face Image Retrieval Using Multiple Features. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12643-2_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12642-5

  • Online ISBN: 978-3-319-12643-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation