NONPLANARITY AND EFFICIENT MULTIPLE FEATURE EXTRACTION

Ernst D. Dickmanns, Hans-Joachim Wuensche

2006

Abstract

A stripe-based image evaluation scheme for real-time vision has been developed allowing efficient detection of the following classes of features: 1. ‘Nonplanarity’ feature for separating image regions treatable by planar shading models from the rest containing textured regions and corners; 2. edges and 3. smoothly shaded regions between edges, and 4. corners for stable 2-D feature tracking. All these features are detected by evaluating receptive fields (masks) with four mask elements shifted through stripes, both in row and column direction. Efficiency stems from re-use of intermediate results in mask elements in neighboring stripes and from coordinated use of these results in different feature extractors. Corner detection with compute-intensive algorithms can be confined to a small (but highly likely) fraction of the images exploiting the efficient nonplanarity feature. Application to road scenes is discussed.

References

  1. Birchfield S 1994. KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker. http://www.ces.clemson.edu/stb/klt/
  2. Dickmanns Dirk 1992. KRONOS, Benutzerhandbuch, 1995, UniBwM/LRT
  3. Dickmanns E.D.; Graefe V.: a) Dynamic monocular machine vision. Machine Vision and Applications, Springer International, Vol. 1, 1988, pp 223-240. b) Applications of dynamic monocular machine vision. (ibid), 1988, pp 241-261
  4. Dickmanns ED, Wuensche HJ 1999. Dynamic Vision for Perception and Control of Motion. In: B. Jaehne, H. Haußenecker, P. Geißler (eds.) Handbook of Computer Vision and Applications, Vol. 3, Academic Press, 1999, pp 569-620
  5. Haralick RM, Shapiro LG 1993. Computer and Robot Vision. Addison-Wesley, 1992 and 1993.
  6. Harris CG, Stephens M 1988. A combined corner and edge detector. Proc. 4th Alvey Vision Conference, pp. 147-153
  7. Hofmann U 2004. Zur visuellen Umfeldwahrnehmung autonomer Fahrzeuge. Dissertation, UniBw Munich, LRT.
  8. Mysliwetz B 1990. Parallelrechner-basierte BildfolgenInterpretation zur autonomen Fahrzeugsteuerung. Dissertation, UniBw Munich, LRT.
  9. Moravec H 1979. Visual Mapping by a Robot Rover. Proc. IJCAI 1079, pp 598-600.
  10. Shi J, Tomasi C 1994. Good Features to Track. Proc. IEEE-Conf. CVPR, pp. 593-600
  11. Tomasi C, Kanade T 1991. Detection and Tracking of Point Features. CMU-Tech.Rep. CMU-CS-91-132
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Paper Citation


in Harvard Style

D. Dickmanns E. and Wuensche H. (2006). NONPLANARITY AND EFFICIENT MULTIPLE FEATURE EXTRACTION . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 198-205. DOI: 10.5220/0001370701980205


in Bibtex Style

@conference{visapp06,
author={Ernst D. Dickmanns and Hans-Joachim Wuensche},
title={NONPLANARITY AND EFFICIENT MULTIPLE FEATURE EXTRACTION},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={198-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001370701980205},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - NONPLANARITY AND EFFICIENT MULTIPLE FEATURE EXTRACTION
SN - 972-8865-40-6
AU - D. Dickmanns E.
AU - Wuensche H.
PY - 2006
SP - 198
EP - 205
DO - 10.5220/0001370701980205