Accurate estimation of fish length in single camera photogrammetry with a fiducial marker

Research output: Contribution to journalArticlepeer-review

Standard Standard

Accurate estimation of fish length in single camera photogrammetry with a fiducial marker. / Monkman, Graham G; Hyder, Kieran; Kaiser, Michel J et al.
In: ICES Journal of Marine Science, Vol. 77, No. 6, 01.11.2020, p. 2245-2254.

Research output: Contribution to journalArticlepeer-review

HarvardHarvard

Monkman, GG, Hyder, K, Kaiser, MJ & Vidal, FP 2020, 'Accurate estimation of fish length in single camera photogrammetry with a fiducial marker', ICES Journal of Marine Science, vol. 77, no. 6, pp. 2245-2254. https://doi.org/10.1093/icesjms/fsz030

APA

Monkman, G. G., Hyder, K., Kaiser, M. J., & Vidal, F. P. (2020). Accurate estimation of fish length in single camera photogrammetry with a fiducial marker. ICES Journal of Marine Science, 77(6), 2245-2254. https://doi.org/10.1093/icesjms/fsz030

CBE

MLA

VancouverVancouver

Monkman GG, Hyder K, Kaiser MJ, Vidal FP. Accurate estimation of fish length in single camera photogrammetry with a fiducial marker. ICES Journal of Marine Science. 2020 Nov 1;77(6):2245-2254. Epub 2019 Mar 14. doi: 10.1093/icesjms/fsz030

Author

Monkman, Graham G ; Hyder, Kieran ; Kaiser, Michel J et al. / Accurate estimation of fish length in single camera photogrammetry with a fiducial marker. In: ICES Journal of Marine Science. 2020 ; Vol. 77, No. 6. pp. 2245-2254.

RIS

TY - JOUR

T1 - Accurate estimation of fish length in single camera photogrammetry with a fiducial marker

AU - Monkman, Graham G

AU - Hyder, Kieran

AU - Kaiser, Michel J

AU - Vidal, Franck P

N1 - This is a pre-copyedited, author-produced version of an article accepted for publication in [insert journal title] following peer review. The version of record [insert complete citation information here] is available online at: https://doi.org/10.1093/icesjms/fsz030

PY - 2020/11/1

Y1 - 2020/11/1

N2 - Abstract Videogrammetry and photogrammetry are increasingly being used in marine science for unsupervised data collection. The camera systems employed are complex, in contrast to “consumer” digital cameras and smartphones carried by potential citizen scientists. However, using consumer cameras in photogrammetry will introduce unknown length estimation errors through both the image acquisition process and lens distortion. This study presents a methodology to achieve accurate 2-dimensional (2-D) total length (TL) estimates of fish without specialist equipment or proprietary software. Photographs of fish were captured with an action camera using a background fiducial marker, a foreground fiducial marker and a laser marker. The geometric properties of the lens were modelled with OpenCV to correct image distortion. TL estimates were corrected for parallax effects using an algorithm requiring only the initial length estimate and known fish morphometric relationships. Correcting image distortion decreased RMSE by 96% and the percentage mean bias error (%MBE) by 50%. Correcting for parallax effects achieved a %MBE of −0.6%. This study demonstrates that the morphometric measurement of different species can be accurately estimated without the need for complex camera equipment, making it particularly suitable for deployment in citizen science and other volunteer-based data collection endeavours.

AB - Abstract Videogrammetry and photogrammetry are increasingly being used in marine science for unsupervised data collection. The camera systems employed are complex, in contrast to “consumer” digital cameras and smartphones carried by potential citizen scientists. However, using consumer cameras in photogrammetry will introduce unknown length estimation errors through both the image acquisition process and lens distortion. This study presents a methodology to achieve accurate 2-dimensional (2-D) total length (TL) estimates of fish without specialist equipment or proprietary software. Photographs of fish were captured with an action camera using a background fiducial marker, a foreground fiducial marker and a laser marker. The geometric properties of the lens were modelled with OpenCV to correct image distortion. TL estimates were corrected for parallax effects using an algorithm requiring only the initial length estimate and known fish morphometric relationships. Correcting image distortion decreased RMSE by 96% and the percentage mean bias error (%MBE) by 50%. Correcting for parallax effects achieved a %MBE of −0.6%. This study demonstrates that the morphometric measurement of different species can be accurately estimated without the need for complex camera equipment, making it particularly suitable for deployment in citizen science and other volunteer-based data collection endeavours.

U2 - 10.1093/icesjms/fsz030

DO - 10.1093/icesjms/fsz030

M3 - Article

VL - 77

SP - 2245

EP - 2254

JO - ICES Journal of Marine Science

JF - ICES Journal of Marine Science

SN - 1054-3139

IS - 6

ER -