Monitoring Motion of Pigs in Thermal Videos

Ruta Gronskyte; Murat Kulahci; Line Katrine Harder Clemmensen

Monitoring Motion of Pigs in Thermal Videos

Ruta Gronskyte, Murat Kulahci, Line Katrine Harder Clemmensen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

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.

Original language	English
Title of host publication	Workshop on Farm Animal and Food Quality Imaging 2013 : Espoo, Finland, June 17, 2013, Proceedings
Place of Publication	Kgs. Lyngby
Publisher	Technical University of Denmark
Publication date	2013
Pages	31-36
Publication status	Published - 2013
Event	Workshop on Farm Animal and Food Quality Imaging 2013 - Espoo, Finland Duration: 17 Jun 2013 → 17 Jun 2013 http://www2.imm.dtu.dk/projects/WFAFQI/

Workshop

Workshop	Workshop on Farm Animal and Food Quality Imaging 2013
Country	Finland
City	Espoo
Period	17/06/2013 → 17/06/2013
Internet address	http://www2.imm.dtu.dk/projects/WFAFQI/

Series	DTU Compute-Technical Report-2013
Number	12
ISSN	1601-2321

Keywords

Optical ow
Blob detection
Multiway principle components
Quality control

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title = "Monitoring Motion of Pigs in Thermal Videos",

abstract = "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{\textquoteright}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.",

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author = "Ruta Gronskyte and Murat Kulahci and Clemmensen, {Line Katrine Harder}",

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publisher = "Technical University of Denmark",

number = "12",

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booktitle = "Workshop on Farm Animal and Food Quality Imaging 2013",

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Gronskyte, R, Kulahci, M & Clemmensen, LKH 2013, Monitoring Motion of Pigs in Thermal Videos. in Workshop on Farm Animal and Food Quality Imaging 2013: Espoo, Finland, June 17, 2013, Proceedings. Technical University of Denmark, Kgs. Lyngby, DTU Compute-Technical Report-2013, no. 12, pp. 31-36, Workshop on Farm Animal and Food Quality Imaging 2013, Espoo, Finland, 17/06/2013.

Monitoring Motion of Pigs in Thermal Videos. / Gronskyte, Ruta; Kulahci, Murat ; Clemmensen, Line Katrine Harder.

Workshop on Farm Animal and Food Quality Imaging 2013: Espoo, Finland, June 17, 2013, Proceedings. Kgs. Lyngby : Technical University of Denmark, 2013. p. 31-36 (DTU Compute-Technical Report-2013; No. 12).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Kulahci, Murat

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AB - 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.

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