Title
Validity of the Microsoft Kinect sensor for assessment of normal walking patterns in pigs
Abstract
Validity of Kinect for assessment of normal walking patterns in pigs was confirmed.Kinect neck elevation trajectories agreed well with a gold standard.The Kinect has potential to be developed into an automated lameness-detection tool. Lameness is a major problem affecting pigs and its detection is subjective and challenging on large farms. Previous research using advanced kinematic gait analysis (Vicon) has established that abnormality in the movement of the axial body during walking is associated with lameness in pigs. Vertical excursion of head and neck was most affected, and increased by +15-58mm in lame compared to normal pigs. However, simpler technology is required to automate lameness detection. In this experiment, walking trajectories of mid-line dorsal body regions of seven normal pigs varying in size were filmed repeatedly within day and between days on two or three occasions within one week. Trajectories were tracked simultaneously using both a 6-camera Vicon system, set up in an array flanking a walkway and detecting reflective markers, and a Microsoft Kinect motion sensor, mounted above the walkway. Four pigs wore a large (height 30mm) reflective marker in the mid-neck region, detectable by both Kinect and Vicon during two days. Two custom-written computer algorithms using the Kinect developer toolkit were produced to (1) follow the large neck marker and (2) enable marker-free tracking of other body regions. Reversed depth data from the Kinect and vertical position data from the Vicon were compared to assess agreement. There was a high positive correlation between the Kinect and Vicon trajectory means of the large neck marker (P
Year
DOI
Venue
2015
10.1016/j.compag.2015.07.003
Computers and Electronics in Agriculture
Keywords
Field
DocType
Kinect,Lameness,Pigs,Automated detection,Motion capture
Motion capture,Computer vision,Kinematics,Dorsum,Gait analysis,Artificial intelligence,Large neck,Motion sensors,Positive correlation,Engineering,Trajectory
Journal
Volume
Issue
ISSN
117
C
0168-1699
Citations 
PageRank 
References 
10
0.69
2
Authors
7
Name
Order
Citations
PageRank
Sophia Stavrakakis1100.69
Wei Li2100.69
Jonathan H. Guy3101.03
Graham Morgan415019.15
Gary Ushaw5399.35
Garth R. Johnson6100.69
Sandra Edwards7333.77