Abstract
Real-time camera tracking is steadily gaining in importance due to the drive from various applications, such as AR (augmented reality), mobile computing, and human–machine interface. In this paper, we describe a real-time camera tracking framework designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that the camera pose estimation is achieved on the basis of a planar object tracking framework. As the camera pose estimation and scene registration is achieved via a non-iterative process, the proposed method is computationally efficient and very fast, and therefore, it can be directly embedded to AR systems running on mobile device platforms. In addition, our system attempts to detect new features assumed to be present on the reference planar surface, so that the system can be operated even when reference features go out of visible range. The accuracy and robustness of the proposed system are verified on the experimental results of several real-time input video streams.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Davison A, Reid I, Morton N, Stasse O (2007) MonoSLAM real-time single camera SLAM. IEEE Trans Pattern Anal Mach Intell 29(6):1052–1067
Lee SH, Lee SK, Choi JS (2009) Real-time camera tracking using a particle filter and multiple feature trackers. In: The first international IEEE consumer electronics society’s game innovation conference, 29–36, London, UK, Aug 2009
Hartley R, Zisserman A (2003) Multiple view geometry in computer vision. Cambridge University Press, Cambridge
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media B.V.
About this paper
Cite this paper
Lee, AH., Lee, SH., Lee, JY., Kim, TE., Choi, JS. (2012). Real-Time Camera Tracking Using Planar Object Detection. In: Kim, K., Ahn, S. (eds) Proceedings of the International Conference on IT Convergence and Security 2011. Lecture Notes in Electrical Engineering, vol 120. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2911-7_34
Download citation
DOI: https://doi.org/10.1007/978-94-007-2911-7_34
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-2910-0
Online ISBN: 978-94-007-2911-7
eBook Packages: EngineeringEngineering (R0)