SMART VISION SENSOR FOR VELOCITY ESTIMATION USING A MULTI-RESOLUTION ARCHITECTURE

Mickael Quelin, Abdesselam Bouzerdoum, Son Lam Phung

Abstract

This paper presents a velocity estimator based on a digital version of the so called Elementary Motion Detector (EMD). Inspired by insect vision, this model benefits from a low complexity motion detection algorithm and is able to estimate velocities in four directions. It can handle noisy images with a pre-filtering step which highlights the important features to be detected. Using a specific velocity tuned detector called Elementary Velocity Detector (EVD) applied to different resolutions of the same input, it gains time efficiency by estimating different speeds in parallel. The responses of the different EVDs are then combined together at the input resolution size.

References

  1. Baker, S., Scharstein, D., Lewis, J., Roth, S., Black, M., and Szeliski, R. (2007). A database and evaluation methodology for optical flow. In Proceedings of the IEEE Int. Conf. Computer Vision, pages 1-8.
  2. Dror, R. O., O'Carroll, D. C., and Laughlin, S. B. (2001). Accuracy of velocity estimation by reichardt correlators. J. Opt. Soc. Am. A, 18(2):241-252.
  3. Harrison, R. R. (2005). A biologically inspired analog ic for visual collision detection. IEEE Trans. Circuits Syst. Regul. Pap., 52(11):2308-2318.
  4. Hassenstein, B. and Reichardt, W. (1956). Functional structure of a mechanism of perception of optical movement. In Rosenblith, W. A., editor, Proc. Int. Cong. Cybern., pages 797-801, Namur.
  5. Horridge, G. A. (1990). A template theory to relate visual processing to digital circuitry. In Proc. R. Soc. Lond., volume Vol. B 239, pages 17-33.
  6. Iida, F. and Lambrinos, D. (2000). Navigation in an autonomous flying robot by using a biologically inpired visual odometer. In Proc. SPIE Sensor Fusion and Decentralized Control in Rob. Syst. III, volume Vol. 4196, pages 86-97.
  7. Jun, Y., Dong-Guang, L., Hui-Min, F., and Zhi-Feng, L. (2004). Moving objects detection by imitating biologic vision based on fly's eyes. In Proc. ROBIO 2004 IEEE Int. Conf. Rob. and Biomim., pages 763-766.
  8. Nakamura, E., Ichimura, M., and Sawada, K. (2002). Fast global motion estimation algorithm based on elementary motion detectors. In Proc. 2002 Int. Conf. Image Processing, volume 2, pages II-297-II-300 vol.2.
  9. Netter, T. and Francescini, N. (2002). A robotic aircraft that follows terrain using a neuromorphic eye. In Proc. IEEE/RSJ Int. Conf. Intel. Rob. and Syst., volume 1, pages 129-134 vol.1.
  10. Nguyen, X., Bouzerdoum, A., and Bogner, R. (1996). Backward tracking of motion trajectories for velocity estimation. In Proc. 1996 Australian and New Zealand Conf. Intelligent Information Systems, pages 338 - 341.
  11. Riabinina, O. and Philippides, A. O. (2009). A model of visual detection of angular speed for bees. J. Theor. Biol., 257(1):61-72.
  12. Sarpeshkar, R., Kramer, J., Indiveri, G., and Koch, C. (1996). Analog vlsi architectures for motion processing: from fundamental limits to system applications. In Proc. IEEE, volume 84, pages 969-987.
  13. Tianguang, Z., Haiyan, W., Borst, A., Kuhnlenz, K., and Buss, M. (2008). An fpga implementation of insectinspired motion detector for high-speed vision systems. In Proc. IEEE Int. Conf. Rob. and Autom., pages 335-340.
  14. Zanker, J. M., Srinivasan, M. V., and Egelhaaf, M. (1999). Speed tuning in elementary motion detectors of the correlation type. Biol. Cybern., 80(2):109-116.
Download


Paper Citation


in Harvard Style

Quelin M., Bouzerdoum A. and Lam Phung S. (2010). SMART VISION SENSOR FOR VELOCITY ESTIMATION USING A MULTI-RESOLUTION ARCHITECTURE . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-028-3, pages 447-452. DOI: 10.5220/0002828804470452


in Bibtex Style

@conference{visapp10,
author={Mickael Quelin and Abdesselam Bouzerdoum and Son Lam Phung},
title={SMART VISION SENSOR FOR VELOCITY ESTIMATION USING A MULTI-RESOLUTION ARCHITECTURE},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={447-452},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002828804470452},
isbn={978-989-674-028-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2010)
TI - SMART VISION SENSOR FOR VELOCITY ESTIMATION USING A MULTI-RESOLUTION ARCHITECTURE
SN - 978-989-674-028-3
AU - Quelin M.
AU - Bouzerdoum A.
AU - Lam Phung S.
PY - 2010
SP - 447
EP - 452
DO - 10.5220/0002828804470452