@inproceedings{0a65a6b65dee4b34b92e2e774b76141e,
title = "Using a 3D camera to evaluate the back posture of dairy cows",
abstract = "In this study, a new computer vision technique to automatically detect lameness in dairy cows was evaluated. A 3D camera system was used to extract the back posture of the animals from top view perspective in a fully automatic way. Four parameters to describe the curvature of the back of the cows were used by a decision tree to classify lame and not lame cows. The experiment was conducted in a commercial Israeli dairy farm. The classification performance of the 3D algorithm was evaluated against the visual locomotion scores given by an expert veterinary. A dataset of 273 cows served to train the model and a dataset of 906 cows to validate it. The analysis led to a sensitivity of 67\% and a specificity of 90\% on a 2-point level scale (lame or not lame) on the validation dataset. These results show that the application of a 3D camera in dairy farming is feasible and can be used in order to develop a fully automatic lameness monitoring tool in dairy farming.",
keywords = "3D camera, Back arch, Dairy cow, Image processing, Lameness detection",
author = "S. Viazzi and \{Van Hertem\}, T. and A. Schlageter-Tello and C. Bahr and Romanini, \{C. E.B.\} and I. Halachmi and C. Lokhorst and D. Berckmans",
year = "2013",
month = jan,
day = "1",
language = "English",
isbn = "9781627486651",
series = "American Society of Agricultural and Biological Engineers Annual International Meeting 2013, ASABE 2013",
publisher = "American Society of Agricultural and Biological Engineers",
pages = "4222--4227",
booktitle = "American Society of Agricultural and Biological Engineers Annual International Meeting 2013, ASABE 2013",
address = "United States",
note = "American Society of Agricultural and Biological Engineers Annual International Meeting 2013 ; Conference date: 21-07-2013 Through 24-07-2013",
}