Dynamic Feature Point Detection for Visual Servoing Using Multiresolution Critical-Point Filters

Brad Chambers, Nicholas Gans, Jérôme Durand, Seth Hutchinson

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

Abstract

In this paper we examine the selection of feature points for visual servoing methods using multiresolution critical-point filters (CPF). With the increased number of feature points made available to us using CPF, we hope to improve the robustness of the system by allowing the algorithm to automatically detect usable feature points on virtually any object without any a priori knowledge of the object. Furthermore, the algorithm will revise these points at each iteration to account for events that may have otherwise caused feature points to be lost and led to the visual servo method ending in failure.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligent Robots and Systems
Pages504-509
Number of pages6
Volume1
StatePublished - 2003
Event2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States
Duration: Oct 27 2003Oct 31 2003

Other

Other2003 IEEE/RSJ International Conference on Intelligent Robots and Systems
CountryUnited States
CityLas Vegas, NV
Period10/27/0310/31/03

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Chambers, B., Gans, N., Durand, J., & Hutchinson, S. (2003). Dynamic Feature Point Detection for Visual Servoing Using Multiresolution Critical-Point Filters. In IEEE International Conference on Intelligent Robots and Systems (Vol. 1, pp. 504-509)