Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Real-Time Localisation and Mapping with Wearable Active Vision
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Face to Face Collaborative AR on Mobile Phones
ISMAR '05 Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality
MonkeyBridge: autonomous agents in augmented reality games
Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic online walls detection for immediate use in AR tasks
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
OutlinAR: an assisted interactive model building system with reduced computational effort
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Online scene modeling for interactive AR applications
ICEC'10 Proceedings of the 9th international conference on Entertainment computing
Wide-area augmented reality using camera tracking and mapping in multiple regions
Computer Vision and Image Understanding
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
A survey of visual, mixed, and augmented reality gaming
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
State of the Art Report on Video-Based Graphics and Video Visualization
Computer Graphics Forum
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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.