Stereo Visual Odometry Without Temporal Filtering

  • Joerg DeigmoellerEmail author
  • Julian Eggert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9796)


Visual Odometry is one of the key technology for navigating and perceiving the environment of an autonomous vehicle. Within the last ten years, a common sense has been established on how to implement high precision and robust systems. This paper goes one step back by avoiding temporal filtering and relying exclusively on pure measurements that have been carefully selected. The focus here is on estimating the ego-motion rather than a detailed reconstruction of the scene. Different approaches for selecting proper 3D-flows (scene flows) are compared and discussed. The ego-motion is computed by a standard P6P-approach encapsulated in a RANSAC environment. Finally, a slim method is proposed that is within the top ranks of the KITTI benchmark without using any filtering method like bundle adjustment or Kalman filtering.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Offenbach am MainGermany

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