Geo-positional Image Forensics through Scene-terrain Registration

P. Chippendale, M. Zanin, M. Dalla Mura

Abstract

In this paper, we explore the topic of geo-tagged photo authentication and introduce a novel forensic tool created to semi-automate the process. We will demonstrate how a photo’s location and time can be corroborated through the correlation of geo-modellable features to embedded visual content. Unlike previous approaches, a machine-vision processing engine iteratively guides users through the photo registration process, building upon available meta-data evidence. By integrating state-of-the-art visual-feature to 3D-model correlation algorithms, camera intrinsic and extrinsic calibration parameters can also be derived in an automatic or semi-supervised interactive manner. Experimental results, considering forensic scenarios, demonstrate the validity of the system introduced.

References

  1. Baatz, G., Saurer, O., Koeser K. and Pollefeys M. (2012). Large Scale Visual Geo-Localization of Images in Mountainous Terrain. In Proc. European Conference on Computer Vision.
  2. Baboud, L., Cadik, M., Eisemann, E. and Seidel, H. (2011). Automatic photo-to-terrain alignment for the annotation of mountain pictures. In IEEE Conference on Computer Vision and Pattern Recognition, 41-48.
  3. Bae, S., Agarwala, A. and Durand, F. (2010). Computational rephotography. In ACM Trans. Graph 29(3), 1-15.
  4. Boehme, R., Freiling, F., Gloe T. and Kirchner, M. (2009). Multimedia forensics is not computer forensics. In Computational Forensics, Lecture Notes in Computer Science, vol. 5718, 90-103.
  5. Casey, E. (2004). Digital evidence and computer crime. In Forensic science, computers and the Internet, Academic Press.
  6. Chippendale, P., Zanin, M. and Andreatta, C. (2009). Collective photography. In Conference for Visual Media Production, 188-194.
  7. Cui, Y. and Ge, S. (2003). Autonomous vehicle positioning with GPS in urban canyon environments. In IEEE Transactions on Robotics and Automation 19(1), 15-25.
  8. Guidi, G., Beraldin, J., Ciofi, S. and Atzeni, C. (2003). Fusion of range camera and photogrammetry: a systematic procedure for improving 3-d models metric accuracy”. In IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 33(4), 667-676.
  9. Hays, J. and Efros, A. (2008). Im2gps: estimating geographic information from a single image. In IEEE Conference on Computer Vision and Pattern Recognition, 1-8.
  10. He, K., Sun, J., Tang, X. (2009). Single image haze removal using dark channel prior. In Computer Vision and Pattern Recognition, 1956-1963.
  11. Karpischek, S., Marforio, C., Godenzi, M., Heuel, S. and Michahelles, F. (2009). Swisspeaks-mobile augmented reality to identify mountains. In Workshop at the International Symposium on Mixed and Augmented Reality.
  12. Kostelec, P. and Rockmore, D. (2008). FFTs on the rotation group. In Journal of Fourier Analysis and Applications 14(2), 145-179.
  13. Leotta, M. and Mundy, J. (2011). Vehicle surveillance with a generic, adaptive, 3d vehicle model. In IEEE Transactions on Pattern Analysis and Machine Intelligence 33(7), 1457-1469.
  14. Li, Z., Zhu, Q. and Gold C. (2005). Digital terrain modeling: principles and methodology. In CRC Press.
  15. Luo, J., Joshi, D., Yu, J. and Gallagher A. (2011). Geotagging in multimedia and computer vision - a survey. In Multimedia Tools and Applications 51, 187- 211.
  16. Paek, J., Kim, J. and Govindan, P. (2010). Energy-e cient rate-adaptive GPS-based positioning for smartphones. In Proceedings of the 8th international conference on Mobile systems, applications, and services, MobiSys 7810, 299-314.
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Paper Citation


in Harvard Style

Chippendale P., Zanin M. and Dalla Mura M. (2013). Geo-positional Image Forensics through Scene-terrain Registration . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 41-47. DOI: 10.5220/0004282300410047


in Bibtex Style

@conference{visapp13,
author={P. Chippendale and M. Zanin and M. Dalla Mura},
title={Geo-positional Image Forensics through Scene-terrain Registration},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={41-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004282300410047},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Geo-positional Image Forensics through Scene-terrain Registration
SN - 978-989-8565-48-8
AU - Chippendale P.
AU - Zanin M.
AU - Dalla Mura M.
PY - 2013
SP - 41
EP - 47
DO - 10.5220/0004282300410047