Weight Estimation of Broilers in Images Using 3D Prior Knowledge

被引:6
|
作者
Jorgensen, Anders [1 ,2 ]
Dueholm, Jacob, V [1 ,2 ]
Fagertun, Jens [2 ]
Moeslund, Thomas B. [1 ]
机构
[1] Aalborg Univ, Aalborg, Denmark
[2] IHFood AS, Copenhagen, Denmark
来源
IMAGE ANALYSIS | 2019年 / 11482卷
关键词
Weight estimation; Statistical shape model; 3D prior knowledge; Model fitting; Broiler;
D O I
10.1007/978-3-030-20205-7_19
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:221 / 232
页数:12
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