Skip to main content

Face Image Retrieval Based on Probe Sketch Using SIFT Feature Descriptors

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7143))

Abstract

This paper presents a feature-based method for matching facial sketch images to face photographs. Earlier approaches calculated descriptors over the whole image and used some transformation and matched them by some classifiers. We present an idea, where descriptors are calculated at selected discrete points (eyes, nose, ears…). This allows us to compare only prominent features. We use SIFT (Scale Invariant Feature Transform) to extract feature descriptors at the annotated points in the sketches and experiment with various methods to retrieve photos. Experimental results demonstrate appreciable matching performances using the presented feature-based methods at a low computational cost.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ke, Y., Sukthankar, R.: PCA-SIFT: A Distinctive Representation for local images descriptors. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), vol. 2 (2004)

    Google Scholar 

  2. Klare, B.F., Li, Z., Jain, A.K.: Matching Forensic Sketch to Mug Shot photos. IEEE Trans. on Pattern Analysis and Machine Intelligence

    Google Scholar 

  3. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active Shape Models-their training and application. Computer Vision and Machine Understanding 61(1), 38–59 (1995)

    Article  Google Scholar 

  4. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE TPAMI 28(12), 514–518, 2037 (2006)

    Article  MATH  Google Scholar 

  5. Zhang, W., Wang, X., Tang, X.: Coupled Information-Theoretic Encoding for Face Photo-Sketch Recognition. In: IEEE Computer Society Conference on Computer Vision and Patter Recognition

    Google Scholar 

  6. Lowe, D.: Distinctive image features from scale-invariant key points. IJCV 60(2), 91–110 (2004)

    Article  Google Scholar 

  7. Mikolajczyk, K., Schmid, C.: A Performance Evaluation of Local Descriptors. IEEE Trans. Pattern Analysis and Machine Intelligence 27(10), 1615–1630 (2005)

    Article  Google Scholar 

  8. Klare, B., Jain, A.: Sketch to Photo Matching: A Feature-Based Approach. In: Proc. SPIE Conf. Biometric Technology for Human Identification VII (2010)

    Google Scholar 

  9. Tang, X., Wang, X.: Face Sketch Recognition. IEEE Trans. Circuits and Systems for Video Technology 14(1), 50–57 (2004)

    Article  Google Scholar 

  10. Wang, X., Tang, X.: Face Photo-Sketch Synthesis and Recognition. IEEE Trans. Pattern Analysis and Machine Intelligence 31(11), 1955–1967 (2009)

    Article  Google Scholar 

  11. Tang, X., Wang, X.: Face Sketch Synthesis and Recognition. In: Proc. IEEE Int’l Conf. Computer Vision, pp. 687–694 (2003)

    Google Scholar 

  12. The University of Manchester, http://personalpages.manchester.ac.uk/staff/timothy.f.cootes/tfc_software.html

  13. Purkait, P., Chanda, B., Kulkarni, S.: A Novel Technique for Sketch to Photo Synthesis. In: 7th International Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2010), Chennai, pp. 224–231 (December 2010)

    Google Scholar 

  14. Jonathon Phillips, P., Wechsler, H., Huang, J., Rauss, P.J.: The FERET database and evaluation procedure for face-recognition algorithms. Image Vision Computer 16(5), 295–306 (1998)

    Article  Google Scholar 

  15. The FERET Database, http://www.itl.nist.gov/iad/humanid/feret/

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

S., R., Atal, K., Arora, A., Purkait, P., Chanda, B. (2012). Face Image Retrieval Based on Probe Sketch Using SIFT Feature Descriptors. In: Kundu, M.K., Mitra, S., Mazumdar, D., Pal, S.K. (eds) Perception and Machine Intelligence. PerMIn 2012. Lecture Notes in Computer Science, vol 7143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27387-2_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-27387-2_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27386-5

  • Online ISBN: 978-3-642-27387-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics