Vision-Based Biometrics for Conservation

  • Sai Ravela
  • James Duyck
  • Chelsea Finn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)

Abstract

Identifying individuals in photographs of animals collected over time is a non-invasive approach that enables ecological studies and conservation planning. Here we propose SLOOP, the first image retrieval system incorporating interactive image processing and matching tools with relevance feedback from crowdsourcing to solve large-scale individual identification for multiple species. One outcome is an advance in matching and image retrieval methodology; another is the creation of a community-based individual identification system that enables conservation planning.

Keywords

Relevance Feedback Relevance Judgement Humpback Whale Image Retrieval System Whale Shark 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Ravela, S.: On Multi-scale Differential Features and their Representations for Recognition and Retrieval. PhD thesis, University of Massachusetts at Amherst (2002)Google Scholar
  2. 2.
    Ravela, S., Gamble, L.: On recognizing individual salamanders. In: Proc. Asian Conference on Computer Vision (ACCV 2004), vol. 2, pp. 741–747 (2004)Google Scholar
  3. 3.
    Gamble, L., Ravela, S., McGarigal, K.: Multi-scale features for identifying individuals in large biological databases: an application of pattern recognition technology to the marbled salamander ambystoma opacum. Journal of Applied Ecology 45(1), 170–180 (2008)CrossRefGoogle Scholar
  4. 4.
    Yang, C., Ravela, S.: Spectral control of viscous alignment for deformation invariant image matching. In: Proceedings of International Conference on Computer Vision, vol. 1, pp. 1303–1310 (2009)Google Scholar
  5. 5.
    Staff: Program will identify skinks. Otago Daily Times (June 2012), http://www.odt.co.nz/news/dunedin/215070/program-will-identify-skinks
  6. 6.
    Kumar, N., Belhumeur, P.N., Biswas, A., Jacobs, D.W., Kress, W.J., Lopez, I.C., Soares, J.V.B.: Leafsnap: A computer vision system for automatic plant species identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part II. LNCS, vol. 7573, pp. 502–516. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Mizroch, S., Beard, J., Lynde, M.: Individual recognition of cetaceans: Use of photo-identification and other techniques to estimate population parameters. In: Hammond, P.S., Mizroch, S.A. (eds.) Computer assisted photo-identification of humpback whales. 12. International Whaling Commission, Cambridge, UK, pp. 63–70 (1990)Google Scholar
  8. 8.
    Araabi, B., Kehtarnavaz, N., McKinney, T., Hillman, G., Wursig, B.: A string matching computer-assisted system for dolphin photoidentification. Annals of Biomedical Engineering 28, 1269–1279 (2000)CrossRefGoogle Scholar
  9. 9.
    Arzoumanian, Z., Holmberg, J., Norman, B.: An astronomical pattern-matching algorithm for computer-aided identification of whale sharks rhincodon typus. Journal of Applied Ecology 42, 999–1011 (2005)CrossRefGoogle Scholar
  10. 10.
    Hiby, L., Lovell, P.: A note on an automated system for matching the callosity patterns on aerial photographs of southern right whales. Journal of Cetacean Research and Management 2, 291–295 (2001)Google Scholar
  11. 11.
    Kelly, M.: Computer-aided photograph matching in studies using individual identification: an example from serengeti cheetahs. Journal of Mammalogy 82, 440–449 (2001)CrossRefGoogle Scholar
  12. 12.
    Runge, J.: Reducing spectral reflections through image inpainting. Master’s thesis, Massachusetts Institute of Technology (2009)Google Scholar
  13. 13.
    Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)CrossRefGoogle Scholar
  14. 14.
    Rangarajan, A., Chui, H., Mjolsness, E., Pappu, S., Davachi, L., Goldman-Rakic, P.S., Duncan, J.S.: A robust point matching algorithm for autoradiograph alignment. Medical Image Analysis 1 (1997)Google Scholar
  15. 15.
    Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press (2004) ISBN: 0521540518 Google Scholar
  16. 16.
    Ravela, S., Duyck, J., Yang, C., Gamble, L.: Sloop system web (June 2009), http://tinyurl.com/mitsloop

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sai Ravela
    • 1
  • James Duyck
    • 1
  • Chelsea Finn
    • 1
  1. 1.Earth Signals and Systems Group Earth, Atmospheric and Planetary SciencesMassachusetts Institute of TechnologyUSA

Personalised recommendations