Paper Info
Title
Ninja on a Plane: Automatic Discovery of Physical Planes for Augmented Reality Using Visual SLAM
Abstract
Most work in visual augmented reality (AR) employs predefined markers or models that simplify the algorithms needed for sensor positioning and augmentation but at the cost of imposing restrictions on the areas of operation and on interactivity. This paper presents a simple game in which an AR agent has to navigate using real planar surfaces on objects that are dynamically added to an unprepared environment. An extended Kalman filter (EKF) simultaneous localisation and mapping (SLAM) framework with automatic plane discovery is used to enable the player to interactively build a structured map of the game environment using a single, agile camera. By using SLAM, we are able to achieve real-time interactivity and maintain rigorous estimates of the system's uncertainty, which enables the effects of high quality estimates to be propagated to other features (points and planes) even if they are outside the camera's current field of view.
Year
DOI
Venue
2007
10.1109/ISMAR.2007.4538840
ISMAR
Keywords
Field
DocType
unprepared environment,game environment,extended kalman filter,visual slam,agile camera,real-time interactivity,simple game,automatic discovery,high quality estimate,physical planes,ar agent,current field,augmented reality,automatic plane discovery,kalman filters,real time,information system,indexing terms,computer vision
Field of view,Interactivity,Computer vision,Extended Kalman filter,Computer graphics (images),Computer science,Kalman filter,Agile software development,Augmented reality,Planar,Artificial intelligence,Simultaneous localisation and mapping
Conference
Citations 
PageRank 
References 
29
1.32
12
Authors
4
Name
Order
Citations
PageRank
Denis Chekhlov116410.61
Andrew P. Gee21398.80
Andrew Calway364554.66
Walterio Mayol-Cuevas4997.48