TR2010-038

Axial Light Field for Curved Mirrors: Reflect Your Perspective, Widen Your View


    •  Taguchi, Y., Agrawal, A.K., Ramalingam, S., Veeraraghavan, A.N., "Axial Light Field for Curved Mirrors: Reflect Your Perspective, Widen Your View", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), DOI: 10.1109/CVPR.2010.5540172, June 2010, pp. 499-506.
      BibTeX TR2010-038 PDF
      • @inproceedings{Taguchi2010jun,
      • author = {Taguchi, Y. and Agrawal, A.K. and Ramalingam, S. and Veeraraghavan, A.N.},
      • title = {Axial Light Field for Curved Mirrors: Reflect Your Perspective, Widen Your View},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2010,
      • pages = {499--506},
      • month = jun,
      • doi = {10.1109/CVPR.2010.5540172},
      • url = {https://www.merl.com/publications/TR2010-038}
      • }
  • Research Area:

    Computer Vision

Mirrors have been used to enable wide field-of-view (FOV) catadioptric imaging. The mapping between the incoming and reflected light rays depends non-linearly on the mirror shape and has been well-studied using caustics. We analyze this mapping using two-plane light field parameterization, which provides valuable insight into the geometric structure of reflected rays. Using this analysis, we study the problem of generating a single-viewpoint virtual perspective image for catadioptric systems, which is unachievable for several common configurations. Instead of minimizing distortions appearing in a single image, we propose to capture all the rays required to generate a virtual perspective by capturing a light field. We consider rotationally symmetric mirrors and show that a traditional planar light field results in significant aliasing artifacts. We propose axial light field, captured by moving the camera along the mirror rotation axis, for efficient sampling and to remove aliasing artifacts. This allows us to computationally generate wide FOV virtual perspectives using a wider class of mirrors than before, without using scene priors to depth estimation. We analyze the relationship between the axial light field parameters and the FOV/resolution of the resulting virtual perspective. Real results using a spherical mirror demonstrate generating 140 degrees FOV virtual perspective using multiple 30 degrees FOV images.

 

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    •  NEWS   CVPR 2010: 8 publications by C. Oncel Tuzel, Tim K. Marks, Yuichi Taguchi, Srikumar Ramalingam, Michael J. Jones and Amit K. Agrawal
      Date: June 13, 2010
      Where: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
      MERL Contacts: Michael Jones; Tim Marks
      Brief
      • The papers "Optimal Coded Sampling for Temporal Super-Resolution" by Agrawal, A.K., Gupta, M., Veeraraghavan, A.N. and Narasimhan, S.G., "Breaking the Interactive Bottleneck in Multi-class Classification with Active Selection and Binary Feedback" by Joshi, A.J., Porikli, F.M. and Papanikolopoulos, N., "Axial Light Field for Curved Mirrors: Reflect Your Perspective, Widen Your View" by Taguchi, Y., Agrawal, A.K., Ramalingam, S. and Veeraraghavan, A.N., "Morphable Reflectance Fields for Enhancing Face Recognition" by Kumar, R., Jones, M.J. and Marks, T.K., "Increasing Depth Resolution of Electron Microscopy of Neural Circuits using Sparse Tomographic Reconstruction" by Veeraraghavan, A., Genkin, A.V., Vitaladevuni, S., Scheffer, L., Xu, S., Hess, H., Fetter, R., Cantoni, M., Knott, G. and Chklovskii, D., "Specular Surface Reconstruction from Sparse Reflection Correspondences" by Sankaranarayanan, A., Veeraraghavan, A.N., Tuzel, C.O. and Agrawal, A.K., "Fast Directional Chamfer Matching" by Liu, M.-Y., Tuzel, C.O., Veeraraghavan, A.N. and Chellappa, R. and "Robust RVM regression using sparse outlier model" by Mitra, K., Veeraraghavan, A. and Chellappa, R. were presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
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