Gronskyte, Ruta3; Kulahci, Murat1; Clemmensen, Line Katrine Harder1
1 Department of Applied Mathematics and Computer Science, Technical University of Denmark2 Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark3 Department of Informatics and Mathematical Modeling, Technical University of Denmark
We propose a new approach for monitoring animal movement in thermal videos. The method distinguishes movements as walking in the expected direction from walking in the opposite direction, stopping or lying down. The method utilizes blob detection combined with opti-cal ow to segment the pigs and extract features which characterize a pig’s movement (direction and speed). Subsequently a multiway princi-pal component analysis is used to analyze the movement features and monitor their development over time. Results are presented in the form of quality control charts of the principal components. The method works on-line with pre-training.
Workshop on Farm Animal and Food Quality Imaging 2013: Espoo, Finland, June 17, 2013, Proceedings, 2013, p. 31-36
Optical ow; Blob detection; Multiway principle components; Quality control
Main Research Area:
Dtu Compute-technical Report-2013
Workshop on Farm Animal and Food Quality Imaging 2013