Literature DB >> 15814144

Validation of a digital video tracking system for recording pig locomotor behaviour.

Nanna M Lind1, Michael Vinther, Ralf P Hemmingsen, Axel K Hansen.   

Abstract

We are introducing a system for automatically tracking pig locomotor behaviour. Transposing methods for the video-based tracking of rodent behaviour engenders several problems. We have therefore improved existing methods, based on image-subtraction, to offer increased flexibility and accuracy in tracking large-sized animals in situations with a constantly changing background. The improved tracking algorithms introduce a reference frame, which does not include the animal and is automatically updated, and implementation of an automatic threshold detection algorithm. This makes the system more robust to the tracking environment, which could even be of the same colour as the animal, and allows the tracking environment to change during recording. We validated the system by estimating the repeatability, accuracy, and basic noise level, and tested the system in different levels of animal activity evoked by administration of apomorphine (APO) to minipigs in an open field test. Seven pigs each received the vehicle and three doses of APO (0.05, 0.1, and 0.3 mg/kg i.m.), and the locomotor behaviour of each session was recorded for 60-min. The calculated coefficient of repeatability was 0.6%, indicating high repeatability and the basic noise level of the tracking system was estimated to be 2%. Administration of the two lowest doses of APO was accompanied by increased locomotor activity of the pigs. Thus, this digital video-based tracking system for automatically tracking the spontaneous locomotor behaviour of pigs is highly reliable and accurate, and was able to detect well-known effects of APO in pig locomotor activity.

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Year:  2004        PMID: 15814144     DOI: 10.1016/j.jneumeth.2004.09.019

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  20 in total

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4.  Visualizing and quantifying movement from pre-recorded videos: The spectral time-lapse (STL) algorithm.

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5.  Quick, Accurate, Smart: 3D Computer Vision Technology Helps Assessing Confined Animals' Behaviour.

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7.  Illumination and Reflectance Estimation with its Application in Foreground Detection.

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8.  MouseMove: an open source program for semi-automated analysis of movement and cognitive testing in rodents.

Authors:  Andre L Samson; Lining Ju; Hyun Ah Kim; Shenpeng R Zhang; Jessica A A Lee; Sharelle A Sturgeon; Christopher G Sobey; Shaun P Jackson; Simone M Schoenwaelder
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9.  Automated tracking to measure behavioural changes in pigs for health and welfare monitoring.

Authors:  Stephen G Matthews; Amy L Miller; Thomas PlÖtz; Ilias Kyriazakis
Journal:  Sci Rep       Date:  2017-12-14       Impact factor: 4.379

10.  Voluntary locomotor activity promotes myogenic growth potential in domestic pigs.

Authors:  Claudia Kalbe; Manuela Zebunke; Dorothea Lösel; Julia Brendle; Steffen Hoy; Birger Puppe
Journal:  Sci Rep       Date:  2018-02-07       Impact factor: 4.379

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