Dynamic 3D surface reconstruction using a hand-held camera

Hao Fan; Lin Qi; Junyu Dong; Gongfa Li; Hui Yu

doi:10.1109/IECON.2018.8592826

Dynamic 3D surface reconstruction using a hand-held camera

Hao Fan
, Lin Qi
, Junyu Dong
, Gongfa Li
, Hui Yu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

445 Downloads (Pure)

Abstract

This paper proposes a dynamic 3D reconstruction method for recovering a surface shape from a set of images that are captured by a hand-held camera. A light source is attached to the camera as a photometric constraint. Thus, we can effectively calculate photometric stereo using the relative moving camera. The key contributions of our work are a robust pixel matching method to build effective correspondences between images for normal estimation, and an optimization method to correct the deviation in the recovered surface shape that is caused by the non- ideal illumination in a close-range lighting condition. Specially we correct the recovered shape by adding an interpolation surface that is estimated using sparse control points from the structure from motion. The effectiveness of our method is verified on real datasets with a digital camera and a smartphone.

Original language	English
Title of host publication	IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3244-3249
Number of pages	6
ISBN (Electronic)	978-1-5090-6684-1, 978-1-5090-6683-4
ISBN (Print)	978-1-5090-6685-8
DOIs	https://doi.org/10.1109/IECON.2018.8592826
Publication status	Published - 31 Dec 2018
Event	44th Annual Conference of the IEEE Industrial Electronics Society - Washington DC, United States Duration: 21 Oct 2018 → 23 Oct 2018 http://www.iecon2018.org/

Publication series

Name	IEEE IECON Proceedings Series
Publisher	IEEE
ISSN (Print)	1553-572X
ISSN (Electronic)	2577-1647

Conference

Conference	44th Annual Conference of the IEEE Industrial Electronics Society
Abbreviated title	IECON 2018
Country/Territory	United States
City	Washington DC
Period	21/10/18 → 23/10/18
Internet address	http://www.iecon2018.org/

Keywords

RCUK
EPSRC
EP/N025849/1

Access to Document

10.1109/IECON.2018.8592826

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Accepted author manuscript (Post-print), 2.06 MB

Cite this

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title = "Dynamic 3D surface reconstruction using a hand-held camera",

abstract = "This paper proposes a dynamic 3D reconstruction method for recovering a surface shape from a set of images that are captured by a hand-held camera. A light source is attached to the camera as a photometric constraint. Thus, we can effectively calculate photometric stereo using the relative moving camera. The key contributions of our work are a robust pixel matching method to build effective correspondences between images for normal estimation, and an optimization method to correct the deviation in the recovered surface shape that is caused by the non- ideal illumination in a close-range lighting condition. Specially we correct the recovered shape by adding an interpolation surface that is estimated using sparse control points from the structure from motion. The effectiveness of our method is verified on real datasets with a digital camera and a smartphone.",

keywords = "RCUK, EPSRC, EP/N025849/1",

author = "Hao Fan and Lin Qi and Junyu Dong and Gongfa Li and Hui Yu",

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doi = "10.1109/IECON.2018.8592826",

language = "English",

isbn = "978-1-5090-6685-8",

series = "IEEE IECON Proceedings Series",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3244--3249",

booktitle = "IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society",

address = "United States",

note = "44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 ; Conference date: 21-10-2018 Through 23-10-2018",

url = "http://www.iecon2018.org/",

}

Fan, H, Qi, L, Dong, J, Li, G & Yu, H 2018, Dynamic 3D surface reconstruction using a hand-held camera. in IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society., 18381943, IEEE IECON Proceedings Series, Institute of Electrical and Electronics Engineers Inc., pp. 3244-3249, 44th Annual Conference of the IEEE Industrial Electronics Society, Washington DC, District of Columbia, United States, 21/10/18. https://doi.org/10.1109/IECON.2018.8592826

Dynamic 3D surface reconstruction using a hand-held camera. / Fan, Hao; Qi, Lin; Dong, Junyu et al.
IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3244-3249 18381943 (IEEE IECON Proceedings Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - This paper proposes a dynamic 3D reconstruction method for recovering a surface shape from a set of images that are captured by a hand-held camera. A light source is attached to the camera as a photometric constraint. Thus, we can effectively calculate photometric stereo using the relative moving camera. The key contributions of our work are a robust pixel matching method to build effective correspondences between images for normal estimation, and an optimization method to correct the deviation in the recovered surface shape that is caused by the non- ideal illumination in a close-range lighting condition. Specially we correct the recovered shape by adding an interpolation surface that is estimated using sparse control points from the structure from motion. The effectiveness of our method is verified on real datasets with a digital camera and a smartphone.

AB - This paper proposes a dynamic 3D reconstruction method for recovering a surface shape from a set of images that are captured by a hand-held camera. A light source is attached to the camera as a photometric constraint. Thus, we can effectively calculate photometric stereo using the relative moving camera. The key contributions of our work are a robust pixel matching method to build effective correspondences between images for normal estimation, and an optimization method to correct the deviation in the recovered surface shape that is caused by the non- ideal illumination in a close-range lighting condition. Specially we correct the recovered shape by adding an interpolation surface that is estimated using sparse control points from the structure from motion. The effectiveness of our method is verified on real datasets with a digital camera and a smartphone.

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KW - EPSRC

KW - EP/N025849/1

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ER -

Dynamic 3D surface reconstruction using a hand-held camera

Abstract

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Conference

Keywords

Access to Document

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Cite this