Sensor Fusion for Augmented Reality
2006 (English)In: Proceedings of the 9th International Conference on Information Fusion, 2006Conference paper (Refereed)
In Augmented Reality (AR), the position and orientation of the camera have to be estimated with high accuracy and low latency. This nonlinear estimation problem is studied in the present paper. The proposed solution makes use of measurements from inertial sensors and computer vision. These measurements are fused using a Kalman filtering framework, incorporating a rather detailed model for the dynamics of the camera. Experiments show that the resulting filter provides good estimates of the camera motion, even during fast movements.
Place, publisher, year, edition, pages
Sensor fusion, Kalman filter, Augmented reality, Computer vision, Inertial navigation
IdentifiersURN: urn:nbn:se:liu:diva-34747DOI: 10.1109/ICIF.2006.301604Local ID: 23072OAI: oai:DiVA.org:liu-34747DiVA: diva2:255595
9th International Conference on Information Fusion, Florence, Italy, July, 2006