By Topic

Plane-dominant object reconstruction for robotic spatial augmented reality

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Changwoo Nam ; School of Computer Science, Kookmin University, Seoul, 136-702, Korea ; Min-Hyuk Sung ; Joo-Haeng Lee ; Junho Kim

We present a simple reconstruction algorithm of a plane-dominant 3D environment for the robotic spatial augmented reality (RSAR). In spatial augmented reality, a projector renders virtual objects onto 3D objects in the real space. To watch the augmented virtual objects from a viewpoint without distortions, the final image should be pre-distorted based on the geometry information of the 3D objects in the real world. In our RSAR setting, we assume that a robot is equipped with the devices such as a projector, low-cost depth cameras, and the sensor of capturing 3D position of the viewpoint. The robot captures the 3D environment with as a point cloud and reconstructs the geometry of 3D objects in the real world with a set of planes. In order that the viewer can see the distortion-free virtual objects, we compute the pre-warped images of virtual objects for a projector. Finally, we provide an efficient algorithm using GPU shaders to compute the pre-warped images for a projector. In experiments, we provide some results of preliminary simulations for our RSAR scenario.

Published in:

Ubiquitous Robots and Ambient Intelligence (URAI), 2011 8th International Conference on

Date of Conference:

23-26 Nov. 2011