Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation
Abstract Autofocus is a fundamental and key problem for modern imaging sensor design. Although this problem has been well studied in single camera literature, unfortunately, little research has been done on large-scale camera arrays. Most of the existing synthetic aperture imaging systems still need...
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doaj-a20ad5978b7b46598382b1eda6340c982020-11-25T03:34:12ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142013-05-011010.5772/5632110.5772_56321Exploiting Loops in the Camera Array for Automatic Focusing Depth EstimationTao Yang0Yanning Zhang1Rui Yu2Ting Chen3 ShaanXi Provincial Key Laboratory of Speech & Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China ShaanXi Provincial Key Laboratory of Speech & Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China School of Electronic Engineering and Computer Science, Queen Marry, University of London, London, UK ShaanXi Provincial Key Laboratory of Speech & Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, ChinaAbstract Autofocus is a fundamental and key problem for modern imaging sensor design. Although this problem has been well studied in single camera literature, unfortunately, little research has been done on large-scale camera arrays. Most of the existing synthetic aperture imaging systems still need to manually select the optimal focus plane when an object moves. Unlike the conventional autofocus method, which sweeps the focus plane to find the maximal contrast, we present a novel optimization framework to handle the above challenges. In particular, we formulate the camera array autofocus problem as a constrained optimization problem by minimizing the temporal and spatial correspondences error subject to global loop constraint. Then this problem is relaxed as a quadratic program and solved using sequential quadratic programming. The experimental results show that the proposed method achieves a better performance compared with the results of traditional methods. To the best of our knowledge, our proposed method is the first optimization framework for solving camera array autofocus problem and it is of great importance to improve the performance of the existing synthetic aperture imaging system.https://doi.org/10.5772/56321 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tao Yang Yanning Zhang Rui Yu Ting Chen |
spellingShingle |
Tao Yang Yanning Zhang Rui Yu Ting Chen Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation International Journal of Advanced Robotic Systems |
author_facet |
Tao Yang Yanning Zhang Rui Yu Ting Chen |
author_sort |
Tao Yang |
title |
Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation |
title_short |
Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation |
title_full |
Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation |
title_fullStr |
Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation |
title_full_unstemmed |
Exploiting Loops in the Camera Array for Automatic Focusing Depth Estimation |
title_sort |
exploiting loops in the camera array for automatic focusing depth estimation |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2013-05-01 |
description |
Abstract Autofocus is a fundamental and key problem for modern imaging sensor design. Although this problem has been well studied in single camera literature, unfortunately, little research has been done on large-scale camera arrays. Most of the existing synthetic aperture imaging systems still need to manually select the optimal focus plane when an object moves. Unlike the conventional autofocus method, which sweeps the focus plane to find the maximal contrast, we present a novel optimization framework to handle the above challenges. In particular, we formulate the camera array autofocus problem as a constrained optimization problem by minimizing the temporal and spatial correspondences error subject to global loop constraint. Then this problem is relaxed as a quadratic program and solved using sequential quadratic programming. The experimental results show that the proposed method achieves a better performance compared with the results of traditional methods. To the best of our knowledge, our proposed method is the first optimization framework for solving camera array autofocus problem and it is of great importance to improve the performance of the existing synthetic aperture imaging system. |
url |
https://doi.org/10.5772/56321 |
work_keys_str_mv |
AT taoyang exploitingloopsinthecameraarrayforautomaticfocusingdepthestimation AT yanningzhang exploitingloopsinthecameraarrayforautomaticfocusingdepthestimation AT ruiyu exploitingloopsinthecameraarrayforautomaticfocusingdepthestimation AT tingchen exploitingloopsinthecameraarrayforautomaticfocusingdepthestimation |
_version_ |
1724560002582052864 |