Standardized 3D test object for multi-camera calibration during animal pose capture.

camera calibration error analysis three-dimensional animal behavior tracking

Journal

Neurophotonics
ISSN: 2329-423X
Titre abrégé: Neurophotonics
Pays: United States
ID NLM: 101632875

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 08 03 2023
revised: 05 10 2023
accepted: 10 10 2023
medline: 9 11 2023
pubmed: 9 11 2023
entrez: 9 11 2023
Statut: ppublish

Résumé

Accurate capture of animal behavior and posture requires the use of multiple cameras to reconstruct three-dimensional (3D) representations. Typically, a paper ChArUco (or checker) board works well for correcting distortion and calibrating for 3D reconstruction in stereo vision. However, measuring the error in two-dimensional (2D) is also prone to bias related to the placement of the 2D board in 3D. We proposed a procedure as a visual way of validating camera placement, and it also can provide some guidance about the positioning of cameras and potential advantages of using multiple cameras. We propose the use of a 3D printable test object for validating multi-camera surround-view calibration in small animal video capture arenas. The proposed 3D printed object has no bias to a particular dimension and is designed to minimize occlusions. The use of the calibrated test object provided an estimate of 3D reconstruction accuracy. The approach reveals that for complex specimens such as mice, some view angles will be more important for accurate capture of keypoints. Our method ensures accurate 3D camera calibration for surround image capture of laboratory mice and other specimens.

Identifiants

pubmed: 37942210
doi: 10.1117/1.NPh.10.4.046602
pii: 23014TNRR
pmc: PMC10629347
doi:

Types de publication

Journal Article

Langues

eng

Pagination

046602

Informations de copyright

© 2023 The Authors.

Références

Curr Opin Neurobiol. 2020 Feb;60:1-11
pubmed: 31791006
Neuron. 2022 Jul 6;110(13):2080-2093.e10
pubmed: 35609615
Curr Opin Neurobiol. 2022 Apr;73:102522
pubmed: 35453000
Nat Commun. 2021 Aug 31;12(1):5188
pubmed: 34465784
J Imaging. 2021 May 13;7(5):
pubmed: 34460683
Nat Neurosci. 2018 Sep;21(9):1281-1289
pubmed: 30127430
Neuron. 2021 Feb 3;109(3):420-437.e8
pubmed: 33340448
Neuron. 2020 Oct 14;108(1):44-65
pubmed: 33058765
Lab Anim (NY). 2021 Sep;50(9):246-254
pubmed: 34326537
Cell Rep. 2021 Sep 28;36(13):109730
pubmed: 34592148
Science. 2020 Apr 3;368(6486):89-94
pubmed: 32241948

Auteurs

Hao Hu (H)

University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, British Columbia, Canada.
University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada.

Roark Zhang (R)

University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, British Columbia, Canada.
University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada.

Tony Fong (T)

University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, British Columbia, Canada.
University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada.

Helge Rhodin (H)

University of British Columbia, Department of Computer Science, Vancouver, British Columbia, Canada.

Timothy H Murphy (TH)

University of British Columbia, Department of Psychiatry, Kinsmen Laboratory of Neurological Research, Vancouver, British Columbia, Canada.
University of British Columbia, Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada.

Classifications MeSH