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Spatial Feature Matching for Visual Odometry: A Parametric Study

[+] Author Affiliations
Garrett M. Clayton, Joshua R. Fabian

Villanova University, Villanova, PA

Paper No. DSCC2013-3913, pp. V003T40A006; 7 pages
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5614-7
  • Copyright © 2013 by ASME


The goal of this paper is to perform a parametric study on a newly developed visual odometry algorithm for use with color-depth (RGB-D) camera pairs, such as the Microsoft Kinect. In this algorithm, features are detected in the color image and converted to 3D points using the depth image. These features are then described by their 3D location and matched across subsequent frames based on spatial proximity. The visual odometry is then calculated using a one-point inverse kinematic solution. The primary contribution of this work is the identification of critical operating parameters associated with the algorithm, the analysis of their effects on the visual odometry performance, and the verification of the analysis using experimentation.

Copyright © 2013 by ASME



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