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Automatic lameness detection based on 3D-video recordings
Year:
2013
Authors :
Alchanatis, Victor
;
.
Antler, Aharon
;
.
Halachmi, Ilan
;
.
Maltz, Ephraim
;
.
Van-Hertem, Tom
;
.
Volume :
Co-Authors:
Van Hertem, T., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel, Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Maltz, E., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Antler, A., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Alchanatis, V., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Schlageter-Tello, A.A., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Lokhorst, C., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Romanini, C.E.B., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Viazzi, S., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Bahr, C., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Berckmans, D., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Halachmi, I., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Facilitators :
From page:
59
To page:
67
(
Total pages:
9
)
Abstract:
Manual locomotion scoring for lameness detection is a time-consuming and subjective procedure. Therefore, the objective of this study is to quantify the classification performance of a computer vision based algorithm for automated lameness scoring. Cow gait recordings were made during four consecutive night-time milking sessions in an Israeli dairy farm with a 3D-camera. A live on-the-spot assessed 5-point locomotion score was the reference for the automatic lameness score evaluation. A dataset of 1436 cows with automatic lameness scores and live locomotion scores was used for calculating classification performance. The analysis of the automatic scores as independent observations led to a correct classification rate of 50.4% on a 5-point level scale. When allowing a 1 unit error on the 5-point level scale, a correct classification rate of 87.6% was obtained. The obtained tolerant binary correct classification rate was 88.6%. The automated lameness detection system obtained a tolerant correct classification rate of 88.6%.
Note:
Related Files :
3-Dimensional
Classification performance
Classification rates
computer vision
Locomotion score
Vision based algorithms
Show More
Related Content
More details
DOI :
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
31778
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 01:05
You may also be interested in
Scientific Publication
Automatic lameness detection based on 3D-video recordings
Van Hertem, T., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel, Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Maltz, E., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Antler, A., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Alchanatis, V., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Schlageter-Tello, A.A., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Lokhorst, C., WageningenUR Livestock Research, P.O. Box 65, NL-8200AB Lelystad, Netherlands
Romanini, C.E.B., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Viazzi, S., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Bahr, C., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Berckmans, D., Division M3-BIORES: Measure, Model and Manage Bioresponses, KU Leuven, Kasteelpark Arenberg 30, BE-3001 Leuven, Belgium
Halachmi, I., Institute of Agricultural Engineering, Agricultural Research Organization (ARO), Volcani Center, PO Box 6, Bet-Dagan IL-50250, Israel
Automatic lameness detection based on 3D-video recordings
Manual locomotion scoring for lameness detection is a time-consuming and subjective procedure. Therefore, the objective of this study is to quantify the classification performance of a computer vision based algorithm for automated lameness scoring. Cow gait recordings were made during four consecutive night-time milking sessions in an Israeli dairy farm with a 3D-camera. A live on-the-spot assessed 5-point locomotion score was the reference for the automatic lameness score evaluation. A dataset of 1436 cows with automatic lameness scores and live locomotion scores was used for calculating classification performance. The analysis of the automatic scores as independent observations led to a correct classification rate of 50.4% on a 5-point level scale. When allowing a 1 unit error on the 5-point level scale, a correct classification rate of 87.6% was obtained. The obtained tolerant binary correct classification rate was 88.6%. The automated lameness detection system obtained a tolerant correct classification rate of 88.6%.
Scientific Publication
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