Weight Estimation of Broilers in Images Using 3D Prior Knowledge

Anders Jørgensen*, Jacob V. Dueholm, Jens Fagertun, Thomas B. Moeslund

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

1 Citationer (Scopus)

Abstrakt

Cameras are already widely used for inspection and monitoring tasks in poultry slaughter houses. In this paper we evaluate the use of computer vision for broiler carcass weight estimation. We compare the use of 2D image features with 3D features extracted from a statistical shape model fitted to the image. The statistical shape model is built from 45 3D scans captured from broiler carcasses collected at a slaughter house. The use of this 3D prior gave a reduction in mean absolute error compared to 2D features alone and achieved an overall mean average percentage error of 3.47%. The algorithm can run real time and was tested on a dataset containing 136,472 images of broilers, captured at a real production site.
OriginalsprogEngelsk
TitelImage Analysis : 21st Scandinavian Conference, SCIA 2019, Norrköping, Sweden, June 11–13, 2019, Proceedings
RedaktørerMichael Felsberg, Per-Erik Forssén, Jonas Unger, Ida-Maria Sintorn
Antal sider12
ForlagSpringer
Publikationsdato1 jan. 2019
Sider221-232
ISBN (Trykt)978-3-030-20204-0
ISBN (Elektronisk)978-3-030-20205-7
DOI
StatusUdgivet - 1 jan. 2019
Begivenhed21st Scandinavian Conference on Image Analysis, SCIA 2019 - Norrköping, Sverige
Varighed: 11 jun. 201913 jun. 2019

Konference

Konference21st Scandinavian Conference on Image Analysis, SCIA 2019
Land/OmrådeSverige
ByNorrköping
Periode11/06/201913/06/2019
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind11482 LNCS
ISSN0302-9743

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