|Center for Robotics and Intelligent Machines, Georgia Tech||GT CoC IC GVU RIM@GT BORG|
please see my MIT page for up-to-date information
Visual OdometryAlso check out my work on visual SLAM and iSAM, my thesis work...
SummaryVisual odometry recovers the relative motion of a camera based on motion flow. Features are typically tracked between frames and a robust estimation algorithm applied to deal with outliers. Our approach further addresses the problem of degenerate data, which commonly occurs due to low textured surfaces, bad lighting conditions with bright areas and shadows, as well as motion blur.
Example sequenceA short sequence of features as tracked by our visual odometry on data acquired at NIST (click on the image for movie - 5MB):
It is well known that standard RANSAC approaches fail when applied to degenerate data. For visual odometry, the three-point algorithm is commonly used, but produces inconsistent results (see figures below). Our approach in contrast provides consistent results.
Last updated: Jan 2, 2010 by kaess @ ieee.org
© 2010 Michael Kaess. All Rights Reserved.