IEICE TRANSACTIONS on Information
Real Time Aerial Video Stitching via Sensor Refinement and Priority Scan
Summary :
The time efficiency of aerial video stitching is still an open problem due to the huge amount of input frames, which usually results in prohibitive complexities in both image registration and blending. In this paper, we propose an efficient framework aiming to stitch aerial videos in real time. Reasonable distortions are allowed as a tradeoff for acceleration. Instead of searching for globally optimized solutions, we directly refine frame positions with sensor data to compensate for the accumulative error in alignment. A priority scan method is proposed to select pixels within overlapping area into the final panorama for blending, which avoids complicated operations like weighting or averaging on pixels. Experiments show that our method can generate satisfying results at very competitive speed.
- Publication
- IEICE TRANSACTIONS on Information Vol.E95-D No.8 pp.2146-2149
- Publication Date
- 2012/08/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E95.D.2146
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Keyword
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Chao LIAO, Guijin WANG, Bei HE, Chenbo SHI, Yongling SHEN, Xinggang LIN, "Real Time Aerial Video Stitching via Sensor Refinement and Priority Scan" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 8, pp. 2146-2149, August 2012, doi: 10.1587/transinf.E95.D.2146.
Abstract: The time efficiency of aerial video stitching is still an open problem due to the huge amount of input frames, which usually results in prohibitive complexities in both image registration and blending. In this paper, we propose an efficient framework aiming to stitch aerial videos in real time. Reasonable distortions are allowed as a tradeoff for acceleration. Instead of searching for globally optimized solutions, we directly refine frame positions with sensor data to compensate for the accumulative error in alignment. A priority scan method is proposed to select pixels within overlapping area into the final panorama for blending, which avoids complicated operations like weighting or averaging on pixels. Experiments show that our method can generate satisfying results at very competitive speed.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E95.D.2146/_p
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@ARTICLE{e95-d_8_2146,
author={Chao LIAO, Guijin WANG, Bei HE, Chenbo SHI, Yongling SHEN, Xinggang LIN, },
journal={IEICE TRANSACTIONS on Information},
title={Real Time Aerial Video Stitching via Sensor Refinement and Priority Scan},
year={2012},
volume={E95-D},
number={8},
pages={2146-2149},
abstract={The time efficiency of aerial video stitching is still an open problem due to the huge amount of input frames, which usually results in prohibitive complexities in both image registration and blending. In this paper, we propose an efficient framework aiming to stitch aerial videos in real time. Reasonable distortions are allowed as a tradeoff for acceleration. Instead of searching for globally optimized solutions, we directly refine frame positions with sensor data to compensate for the accumulative error in alignment. A priority scan method is proposed to select pixels within overlapping area into the final panorama for blending, which avoids complicated operations like weighting or averaging on pixels. Experiments show that our method can generate satisfying results at very competitive speed.},
keywords={},
doi={10.1587/transinf.E95.D.2146},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - Real Time Aerial Video Stitching via Sensor Refinement and Priority Scan
T2 - IEICE TRANSACTIONS on Information
SP - 2146
EP - 2149
AU - Chao LIAO
AU - Guijin WANG
AU - Bei HE
AU - Chenbo SHI
AU - Yongling SHEN
AU - Xinggang LIN
PY - 2012
DO - 10.1587/transinf.E95.D.2146
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2012
AB - The time efficiency of aerial video stitching is still an open problem due to the huge amount of input frames, which usually results in prohibitive complexities in both image registration and blending. In this paper, we propose an efficient framework aiming to stitch aerial videos in real time. Reasonable distortions are allowed as a tradeoff for acceleration. Instead of searching for globally optimized solutions, we directly refine frame positions with sensor data to compensate for the accumulative error in alignment. A priority scan method is proposed to select pixels within overlapping area into the final panorama for blending, which avoids complicated operations like weighting or averaging on pixels. Experiments show that our method can generate satisfying results at very competitive speed.
ER -
English
