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Proceedings Paper

Virtual-real spatial information visualization registration using affine representations
Author(s): Xueling Wu; Fu Ren
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Paper Abstract

Virtual-real registration in Outdoor Augmented Reality is committed to enhance user's spatial cognition by overlaying virtual geographical objects on real scene. According to analyze fiducial detection registration method in indoor AR, for the purpose of avoiding complex and tedious process of position tracking and camera calibration in traditional registration methods, it puts forward and practices a virtual-real spatial information visualization registration method using affine representations. Based on the observation from Koenderink and van Doorn, Ullman and Basri in 1991 which is given a set of four or more non-coplanar 3D points, the projection of all points in the set can be computed as a linear combination of the projection of just four of the points, it sets up global affine coordinate system in light of world coordinates, camera coordinates and virtual coordinates and extracts four feature points from scene image and calculates the global affine coordinates of key points of virtual objects. Then according to a linear homogeneous coordinates of the four feature point's projection, it calculates projection pixel coordinates of key points of virtual objects. In addition, it proposes an approach to obtain pixel relative depth for hidden surface removal. Finally, by a case study, it verifies the feasibility and efficiency of the registration methods. The method would not only explore a new research direction for Geographical Information Science, but also would provide location-based information and services for outdoor AR.

Paper Details

Date Published: 15 October 2009
PDF: 8 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74920W (15 October 2009); doi: 10.1117/12.837441
Show Author Affiliations
Xueling Wu, China Univ. of Geosciences (China)
Fu Ren, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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