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Abstract
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.
Originalsprog | Engelsk |
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Titel | Image Analysis : 21st Scandinavian Conference, SCIA 2019, Norrköping, Sweden, June 11–13, 2019, Proceedings |
Redaktører | Michael Felsberg, Per-Erik Forssén, Jonas Unger, Ida-Maria Sintorn |
Antal sider | 12 |
Forlag | Springer |
Publikationsdato | 1 jan. 2019 |
Sider | 221-232 |
ISBN (Trykt) | 978-3-030-20204-0 |
ISBN (Elektronisk) | 978-3-030-20205-7 |
DOI | |
Status | Udgivet - 1 jan. 2019 |
Begivenhed | 21st Scandinavian Conference on Image Analysis, SCIA 2019 - Norrköping, Sverige Varighed: 11 jun. 2019 → 13 jun. 2019 |
Konference
Konference | 21st Scandinavian Conference on Image Analysis, SCIA 2019 |
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Land/Område | Sverige |
By | Norrköping |
Periode | 11/06/2019 → 13/06/2019 |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 11482 LNCS |
ISSN | 0302-9743 |
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