Abstract
If the geometry of a marker is known and camera parameters are available, it is possible to recover a camera pose. The transformation between a camera and a marker is defined relative to the local coordinate system of the marker. This paper proposes a real-time camera tracking method using multiple markers while the camera is allowed to move freely in a 3D space. We utilize multiple markers to improve the accuracy of the pose estimation. We also present a coordinate registration algorithm to obtain a global optimal camera pose from local transformations of multiple markers. For the registration, a reference marker is automatically chosen among multiple markers and the global camera pose is computed using all local transforms weighted by marker detection confidence rates. Experimental results show that the proposed method provides more accurate camera poses than those from other methods.
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References
Abdullah, J., Martinez, K.: Camera self-calibration for the artoolkit. In: Proceedings of First International Augmented Reality Toolkit Workshop, pp. 84–88 (2002)
Malbezin, P., Piekarski, W., Thomas, B.: Measuring artoolkit accuracy in lon distance tracking experiments. In: Proceedings of First International Augmented Reality Toolkit Workshop (2002)
eddine Ababsa, F., Mallem, M.: Robust camera pose estimation using 2d fiducials tracking for real-time augmented reality systems. In: VRCAI 2004, New York, NY, USA, pp. 431–435. ACM Press, New York (2004)
Bianchi, G., Wengert, C., Harders, M., Cattin, P., Szekely, G.: Camera-marker alignment framework and comparison with hand-eye calibration for augmented reality applications. In: ISMAR 2005, Washington, DC, USA, pp. 188–189. IEEE Computer Society, Los Alamitos (2005)
Micilotta, A.S., Ong, E.J., Bowden, R.: Real-time upper body 3d pose estimation from a single uncalibrated camera. In: Eurographics, pp. 41–44 (2005)
Skrypnyk, I., Lowe, D.G.: Scene modelling, recognition and tracking with inv riant image features. In: ISMAR 2004, pp. 110–119 (2004)
Kanbara, M., Yokoya, N.: Real-time estimation of light source environment for photorealistic augmented reality. In: ICPR, os Alamitos, CA, USA, vol. 2, pp. 911–914. IEEE Computer Society, Los Alamitos (2004)
Ledermann, F., Reitmayr, G., Schmalstieg, D.: Dynamically shared optical tracking. In: ART 2002. IEEE Computer Society, Los Alamitos (2002)
Uematsu, Y., Saito, H.: Ar registration by merging multiple planar markers at arbitrary positions and poses via projective space. In: ICAT 2005, pp. 48–55 (2005)
Zauner, J., Haller, M.: Authoring of mixed reality applications including multimarker calibration for mobile devices. In: EGVE 2004, Grenoble, France, pp. 87–90 (2004)
Kato, H., Billinghurst, M.: Marker tracking and hmd calibration for a video-based augmented reality conferencing system. In: IWAR 1999, Washington, DC, USA, p. 85. IEEE Computer Society, Los Alamitos (1999)
Fiala, M.: Artag, a fiducial marker system using digital techniques. In: CVPR 2005, Washington, DC, USA, pp. 590–596. IEEE Computer Society, Los Alamitos (2005)
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© 2006 Springer-Verlag Berlin Heidelberg
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Yoon, JH., Park, JS., Kim, C. (2006). Increasing Camera Pose Estimation Accuracy Using Multiple Markers. In: Pan, Z., Cheok, A., Haller, M., Lau, R.W.H., Saito, H., Liang, R. (eds) Advances in Artificial Reality and Tele-Existence. ICAT 2006. Lecture Notes in Computer Science, vol 4282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941354_25
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DOI: https://doi.org/10.1007/11941354_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49776-9
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