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Vision-Based Obstacle Avoidance Using SIFT Features

  • Aaron Chavez
  • David Gustafson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5876)

Abstract

This paper presents a vision-based collision detection algorithm. Our approach is similar to optic flow-based approaches, except that we are working at a feature level instead of a pixel level. The algorithm analyzes a pair of images taken from a moving camera at different times. Then, it recognizes imminent collisions by analyzing the change in scale and location of SIFT features in the pair of images. We have evaluated the performance of this algorithm and present our experimental results.

Keywords

Local navigation obstacle avoidance vision-based navigation SIFT 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Aaron Chavez
    • 1
  • David Gustafson
    • 1
  1. 1.Department of Computer ScienceKansas State UniversityManhattan

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