Locomotion traits of dairy cows from overhead three-dimensional video

Abdul Jabbar, Khalid; Hansen, Mark F; Smith, Melvyn; Smith, Lyndon

Abstract

We investigate two locomotion traits in dairy cows from overhead 3D video to observe lameness trends. Detecting lameness -particularly at an early stage- is important in order to allow early treatment which maximizes detection benefits. The proposed physical setup is covert, non intrusive and it facilitates full autonomy; therefore, it could be implemented on a large-scale or daily-basis with high accuracy. The algorithm automatically tracks features to key regions (i.e. spine, hook bones) using shape index and curvedness measure from the 3D map. The gait asymmetry trait is analysed in the form of a dynamic novel proxy derived from the pelvic height movements, as the animal walks. We have found this proxy sensitive to early lameness trends. The back arch trait is analysed using a fitted polynomial in the extracted spine region. The proposed methods in this paper could be implemented on other cattle breeds, equine or other quadruped animals for the purposes of locomotion assessment.

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: Visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 23rd International Conference on Pattern Recognition (ICPR)
• Start Date: Dec 4, 2016
• End Date: Dec 4, 2016
• Acceptance Date: Sep 8, 2016
• Publication Date: Jan 1, 2016
• Deposit Date: Oct 3, 2016
• Peer Reviewed: Peer Reviewed
• Keywords: dairy cows, three-dimensional visualisation, 3D
• Public URL: https://uwe-repository.worktribe.com/output/916069
• Publisher URL: http://ieeexplore.ieee.org/Xplore/home.jsp
• Related Public URLs: http://homepages.inf.ed.ac.uk/rbf/vaib16.html
• Additional Information: Title of Conference or Conference Proceedings : Visual observation and analysis of Vertebrate And Insect Behavior (VAIB), 23rd International Conference on Pattern Recognition (ICPR)
• Contract Date: Oct 3, 2016