Absolute pose estimation using multiple forms of correspondence from RGB-D frames (Source codes released!!!)

by Shuda Li and Andrew Calway
University of Bristol, UK
accepted by IEEE Intl. Conf. on Robotics and Automation (ICRA), 2016


We describe a new approach to absolute pose estimation from noisy and outlier contaminated matching point sets for RGB-D sensors. We show that by integrating multiple forms of correspondence based on 2-D and 3-D points and surface normals gives more precise, accurate and robust pose estimates. This is because it gives more constraints than using one form alone and increases the available measurements, especially when dealing with sparse matching sets. We demonstrate the approach by incorporating it within a RANSAC algorithm and introduce a novel direct least-square approach to calculate pose estimates. Results from experiments on synthetic and real data demonstrate improved performance over existing methods.



About Shuda Li

Dr Shuda Li -------------------------------- Computer Vision Group Room 1.15 Merchant Venturers Building Woodland Road the University of Bristol Bristol BS8 1UB United Kingdom --------------------------------- Email: lishuda1980@gmail.com csxsl@bristol.ac.uk csxsl@compsci.bristol.ac.uk web: http://www.cs.bris.ac.uk/~csxsl/ Fax: +44 (0)117 954 5208 ---------------------------------
This entry was posted in Uncategorized. Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s