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3D Point Cloud Matching Based Selfie Generation for Chang'e-5.

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Title: 3D Point Cloud Matching Based Selfie Generation for Chang'e-5.
Authors: Chen, Xiao-Rui1 (AUTHOR) chenxiaorui@zju.edu.cn, Yang, Meng-Fei2 (AUTHOR) yangmf@bice.org.cn, Zhang, Gao3 (AUTHOR) zgao501@sina.com, Zhang, Wu3 (AUTHOR) chunll501@sina.com, Peng, Jing3 (AUTHOR) 13911316498@139.com, Gu, Zheng3 (AUTHOR) cascgu@163.com, Deng, Xiang-Jin3 (AUTHOR) dengxiangjin@sina.com, Yang, Liu-Zhi1 (AUTHOR) 154688609@qq.com, Yang, Fei1 (AUTHOR) mufengcj@outlook.com, Yang, Yun1 (AUTHOR) syby119@126.com, Sun, Shou-Qian1 (AUTHOR) ssq@zju.edu.cn, Tong, Ruo-Feng1 (AUTHOR) trf@zju.edu.cn, Tang, Min1 (AUTHOR) tang_m@zju.edu.cn
Source: Journal of Computer Science & Technology (10009000). Jan2025, Vol. 40 Issue 1, p85-98. 14p.
Subjects: Artificial intelligence, Point cloud, Image processing, Image registration, Algorithms
Abstract: Generating selfie images on the surface of a celestial body poses several challenges, including the position of the robotic arm, camera field of view, and limited shooting time. To address these challenges, the PCMIS (3D Point Cloud Matching Based Image Stitching) algorithm is designed, along with a corresponding shooting plan. This algorithm establishes a correspondence between depth and color information, enabling the generation of stitching views under any given view parameter. Furthermore, the algorithm is accelerated using GPU processing, resulting in a significant reduction in stitching time. The algorithm is successfully applied to generate selfie images for the Chang'e-5 mission. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computer Science & Technology (10009000) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
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DbLabel: Engineering Source
An: 183641602
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: 3D Point Cloud Matching Based Selfie Generation for Chang'e-5.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Xiao-Rui%22">Chen, Xiao-Rui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chenxiaorui@zju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Meng-Fei%22">Yang, Meng-Fei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> yangmf@bice.org.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Gao%22">Zhang, Gao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> zgao501@sina.com</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Wu%22">Zhang, Wu</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> chunll501@sina.com</i><br /><searchLink fieldCode="AR" term="%22Peng%2C+Jing%22">Peng, Jing</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> 13911316498@139.com</i><br /><searchLink fieldCode="AR" term="%22Gu%2C+Zheng%22">Gu, Zheng</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> cascgu@163.com</i><br /><searchLink fieldCode="AR" term="%22Deng%2C+Xiang-Jin%22">Deng, Xiang-Jin</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> dengxiangjin@sina.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Liu-Zhi%22">Yang, Liu-Zhi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> 154688609@qq.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Fei%22">Yang, Fei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mufengcj@outlook.com</i><br /><searchLink fieldCode="AR" term="%22Yang%2C+Yun%22">Yang, Yun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> syby119@126.com</i><br /><searchLink fieldCode="AR" term="%22Sun%2C+Shou-Qian%22">Sun, Shou-Qian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ssq@zju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Tong%2C+Ruo-Feng%22">Tong, Ruo-Feng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> trf@zju.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Tang%2C+Min%22">Tang, Min</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> tang_m@zju.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Computer+Science+%26+Technology+%2810009000%29%22">Journal of Computer Science & Technology (10009000)</searchLink>. Jan2025, Vol. 40 Issue 1, p85-98. 14p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Point+cloud%22">Point cloud</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Image+registration%22">Image registration</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Generating selfie images on the surface of a celestial body poses several challenges, including the position of the robotic arm, camera field of view, and limited shooting time. To address these challenges, the PCMIS (3D Point Cloud Matching Based Image Stitching) algorithm is designed, along with a corresponding shooting plan. This algorithm establishes a correspondence between depth and color information, enabling the generation of stitching views under any given view parameter. Furthermore, the algorithm is accelerated using GPU processing, resulting in a significant reduction in stitching time. The algorithm is successfully applied to generate selfie images for the Chang'e-5 mission. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Computer Science & Technology (10009000) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=183641602
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        Value: 10.1007/s11390-024-3667-6
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      – Code: eng
        Text: English
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        PageCount: 14
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        Type: general
      – SubjectFull: Point cloud
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      – SubjectFull: Image processing
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      – SubjectFull: Image registration
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              Text: Jan2025
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