FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Realtime Visualization of Monocular Data for 3D Reconstruction
CRV '08 Proceedings of the 2008 Canadian Conference on Computer and Robot Vision
Ninja on a Plane: Automatic Discovery of Physical Planes for Augmented Reality Using Visual SLAM
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
ISMAR '09 Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality
In-place 3D sketching for authoring and augmenting mechanical systems
ISMAR '09 Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality
Discovering Higher Level Structure in Visual SLAM
IEEE Transactions on Robotics
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Augmented reality applications require 3D model of environment to provide even more realistic experience. Unfortunately, however, most of researches on 3D modeling have been restricted to an offline process up to now, which conflicts with characteristics of AR such as realtime and online experience. In addition, it is barely possible not only to generate 3D model of whole world in advance but also trasfer the burden of 3D model generation to a user, which limits the usability of AR. Thus, it is required to draw the 3D model generation to an online stage from an offline stage. In this paper, we propose an online scene modeling method to generate 3D model of a scene, based on the keyframe-based SLAM which supports AR experience even in an unknown scene by generating a map of 3D points. The scene modeling process in this paper is a little computationally expensive in terms of real-time but it doesn't restrict real-time property of AR because it is executed on a background process. Therefore, a user will be provided with an interactive AR applications that support interactions between the real and virtual world even in an unknown environment.