@inproceedings{b911960baa9d4a1898b162dd31383074,
title = "Fast omni-image unwarping using pano-mapping pointers array",
abstract = "Omni-cameras are becoming ubiquitous in several applications that require a wide field of view (such as 3D reconstruction, video surveillance, robot vision, etc.) and thus the need to reduce computational time during omni-image un-warping. In this paper a computationally efficient alternative referred as pano-mapping pointers array (PMPA) is proposed. First, a buffer is created to save the omni-image. Then, a PMPA is created, where each entry points to a specific place in the buffer depending on the interpolation desired (nearest neighbors or bilinear interpolation). Finally, using the PMPA we unwarp the omni-image. The PMPA is created once for an omni-camera, interpolation method and panoramic image resolution. Experiments on a standard computer demonstrate that the proposed method is about 5.8 (nearest neighbors) and 2.1 (bilinear interpolation) times faster than the classic pano-mapping table method and about 1.7 (nearest neighbors) times faster than the one-eighth pano-mapping table method.",
keywords = "Omnidirectional, image processing, unwarping",
author = "Jaime Reategui and Paul Rodriguez and Nicolas Ragot",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.",
year = "2014",
month = jan,
day = "28",
doi = "10.1109/ICIP.2014.7026175",
language = "English",
series = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5811--5815",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
}