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Weight Estimation of Broilers in Images Using 3D Prior Knowledge

机译:使用3D先前知识重量估计图像中的肉鸡的重量估计

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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.
机译:相机已经广泛用于家禽屠宰场中的检查和监控任务。在本文中,我们评估了计算机视觉对肉鸡胴体重量估计的使用。我们比较使用2D图像特征,并从安装到图像的统计形状模型中提取的3D功能。统计形状模型由在屠宰场收集的肉鸡尸体捕获的35次扫描建造。与2D特征相比,使用该3D的使用使得平均绝对误差减少,并实现了3.47%的总体平均百分比误差。该算法可以运行实时,并在包含在实际生产现场捕获的肉鸡的数据集上测试数据集。

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