TY - GEN
T1 - Fast omni-image unwarping using pano-mapping pointers array
AU - Reategui, Jaime
AU - Rodriguez, Paul
AU - Ragot, Nicolas
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/28
Y1 - 2014/1/28
N2 - 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.
AB - 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.
KW - Omnidirectional
KW - image processing
KW - unwarping
UR - http://www.scopus.com/inward/record.url?scp=84983132748&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7026175
DO - 10.1109/ICIP.2014.7026175
M3 - Conference contribution
AN - SCOPUS:84983132748
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 5811
EP - 5815
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -