Discovering the Structure of a Planar Mirror System from Multiple Observations of a Single Point
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Raskar_Discovering the.pdf
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Author(s)
Reshetouski, Ilya
Manakov, Alkhazur
Bandhari, Ayush
Raskar, Ramesh
Seidel, Hans-Peter
Ihrke, Ivo
Bhandari, Ayush
Date Issued
June 2013
Journal
2013 IEEE Conference on Computer Vision and Pattern Recognition
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Reshetouski, Ilya, Alkhazur Manakov, Ayush Bandhari, Ramesh Raskar, Hans-Peter Seidel, and Ivo Ihrke. “Discovering the Structure of a Planar Mirror System from Multiple Observations of a Single Point.” 2013 IEEE Conference on Computer Vision and Pattern Recognition (June 2013), 23-28 June, Portland, Oregon, USA.
Version
Author's final manuscript
Abstract
We investigate the problem of identifying the position of a viewer inside a room of planar mirrors with unknown geometry in conjunction with the room's shape parameters. We consider the observations to consist of angularly resolved depth measurements of a single scene point that is being observed via many multi-bounce interactions with the specular room geometry. Applications of this problem statement include areas such as calibration, acoustic echo cancelation and time-of-flight imaging. We theoretically analyze the problem and derive sufficient conditions for a combination of convex room geometry, observer, and scene point to be reconstruct able. The resulting constructive algorithm is exponential in nature and, therefore, not directly applicable to practical scenarios. To counter the situation, we propose theoretically devised geometric constraints that enable an efficient pruning of the solution space and develop a heuristic randomized search algorithm that uses these constraints to obtain an effective solution. We demonstrate the effectiveness of our algorithm on extensive simulations as well as in a challenging real-world calibration scenario.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CVPR.2013.19
