Comparison of approaches to egomotion computation

Tina Y. Tian, Carlo Tomasi, David J. Heeger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We evaluated six algorithms for computing egomotion from image velocities. We established benchmarks for quantifying bias and sensitivity to noise, and for quantifying the convergence properties of those algorithms that require numerical search. Our simulation results reveal some interesting and surprising results. First, it is often written in the literature that the egomotion problem is difficult because translation (e.g., along the X-axis) and rotation (e.g., about the Y-axis) produce similar image velocities. We found, to the contrary, that the bias and sensitivity of our six algorithms are totally invariant with respect to the axis of rotation. Second, it is also believed by some that fixating helps to make the egomotion problem easier. We found, to the contrary, that fixating does not help when the noise is independent of the image velocities. Fixation does help if the noise is proportional to speed, but this is only for the trivial reason that the speeds are slower under fixation. Third, it is widely believed that increasing the field of view will yield better performance. We found, to the contrary, that this is not necessarily true.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE
Pages315-320
Number of pages6
StatePublished - 1996
EventProceedings of the 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - San Francisco, CA, USA
Duration: Jun 18 1996Jun 20 1996

Other

OtherProceedings of the 1996 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CitySan Francisco, CA, USA
Period6/18/966/20/96

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Tian, T. Y., Tomasi, C., & Heeger, D. J. (1996). Comparison of approaches to egomotion computation. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 315-320). IEEE.