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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Main Authors: Tao Yang, Yanning Zhang, Rui Yu, Ting Chen
Format: Article
Language:English
Published: SAGE Publishing 2013-05-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/56321
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spelling 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
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