@inproceedings{3e3451b7d6324074ab8a316344ce9cdb,
title = "Automatic back posture evaluation in dairy cows using a 3D camera",
abstract = "This study tested and evaluated a computer vision technique to automatically detect lameness in dairy cows. A three-dimensional camera system was used to extract the back posture of the animals automatically from a top view perspective. Four parameters to describe the curvature of the cow's back were used in a decision tree to classify cows as lame or not lame. The experiment was conducted at a commercial Israeli dairy farm and a dataset of 273 cows was recorded by the three-dimensional camera. The classification performance of the 3D algorithm was evaluated against the visual locomotion scores awarded by an expert veterinarian. The analysis resulted in a sensitivity of 75.0\% and a specificity of 98\% on a 2-point level scale (lame or not lame). These results show that it is possible to use a 3D camera in dairy farming in order to develop a fully automatic lameness monitoring tool for dairy farming.",
keywords = "Back posture, Computer vision, Dairy cow, Lameness",
author = "S. Viazzi and \{Van Hertem\}, T. and Romanini, \{C. E.B.\} and C. Bahr and I. Halachmi and Tello, \{A. Schlageter\} and C. Lokhorst and D. Rozen and D. Berckmans",
year = "2013",
month = jan,
day = "1",
language = "English",
isbn = "9789088263330",
series = "Precision Livestock Farming 2013 - Papers Presented at the 6th European Conference on Precision Livestock Farming, ECPLF 2013",
publisher = "Katholieke Universiteit Leuven",
pages = "83--91",
booktitle = "Precision Livestock Farming 2013 - Papers Presented at the 6th European Conference on Precision Livestock Farming, ECPLF 2013",
note = "6th European Conference on Precision Livestock Farming, ECPLF 2013 ; Conference date: 10-09-2013 Through 12-09-2013",
}