Ninja on a Plane: Automatic Discovery of Physical Planes for Augmented Reality Using Visual SLAM

D Chekhlov, AP Gee, AD Calway, WW Mayol-Cuevas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

52 Citations (Scopus)

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.
Translated title of the contributionNinja on a Plane: Automatic Discovery of Physical Planes for Augmented Reality Using Visual SLAM
Original languageEnglish
Title of host publicationInternational Symposium on Mixed and Augmented Reality
Publication statusPublished - Nov 2007

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the International Symposium on Mixed and Augmented Reality

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