Publication
D-TrackāA semi-automatic 3D video-tracking technique to analyse movements and routines of aquatic animals with application to captive dolphins
| dc.contributor.author | Lopes, PatrĆcia Rachinas | |
| dc.contributor.author | Ribeiro, Ricardo | |
| dc.contributor.author | Santos, Manuel Eduardo dos | |
| dc.contributor.author | Costa, Rui Miguel | |
| dc.date.accessioned | 2019-03-12T15:00:47Z | |
| dc.date.available | 2019-03-12T15:00:47Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Scoring and tracking animal movements manually is a time consuming and subjective process, susceptible to errors due to fatigue. Automated and semi-automated video-based tracking methods have been developed to overcome the errors and biases of manual analyses. In this manuscript we present D-Track, an open-source semi-automatic tracking system able to quantify the 3D trajectories of dolphins, non-invasively, in the water. This software produces a three-dimensional reconstruction of the pool and tracks the animal at different depths, using standard cameras. D-Track allows the determination of spatial preferences of the animals, their speed and its variations, and the identification of behavioural routines. We tested the system with two captive dolphins during different periods of the day. Both animals spent around 85% of the time at the surface of the Deep Area of their pool (5-meters depth). Both dolphins showed a stable average speed throughout 31 sessions, with slow speeds predominant (maximum 1.7 ms-1). Circular swimming was highly variable, with significant differences in the size and duration of the "circles", between animals, within-animals and across sessions. The D-Track system is a novel tool to study the behaviour of aquatic animals, and it represents a convenient and inexpensive solution for laboratories and marine parks to monitor the preferences and routines of their animals. | pt_PT |
| dc.description.sponsorship | Howard Hughes Medical Institute | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1371/journal.pone.0201614 | pt_PT |
| dc.identifier.issn | 19326203 | |
| dc.identifier.uri | http://hdl.handle.net/10400.12/6945 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Public Library of Science | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | pt_PT |
| dc.subject | Animals | pt_PT |
| dc.subject | Behavior | pt_PT |
| dc.subject | Dolphins | pt_PT |
| dc.subject | Imaging, Three-Dimensional | pt_PT |
| dc.subject | Male | pt_PT |
| dc.subject | Software | pt_PT |
| dc.subject | Swimming | pt_PT |
| dc.subject | Swimming Pools | pt_PT |
| dc.subject | Video Recording | pt_PT |
| dc.title | D-TrackāA semi-automatic 3D video-tracking technique to analyse movements and routines of aquatic animals with application to captive dolphins | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F73886%2F2010/PT | |
| oaire.citation.conferencePlace | United States | pt_PT |
| oaire.citation.endPage | 12 | pt_PT |
| oaire.citation.issue | 8 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | PLoS ONE | pt_PT |
| oaire.citation.volume | 13 | pt_PT |
| oaire.fundingStream | SFRH | |
| person.familyName | de Noronha Gamito Afonso dos Santos | |
| person.givenName | Manuel Eduardo | |
| person.identifier.ciencia-id | 4E18-0CBD-48E0 | |
| person.identifier.orcid | 0000-0001-8225-9398 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | FundaĆ§Ć£o para a CiĆŖncia e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | b7ab5e0d-61c3-4044-9cb5-73bdb6ed372d | |
| relation.isAuthorOfPublication.latestForDiscovery | b7ab5e0d-61c3-4044-9cb5-73bdb6ed372d | |
| relation.isProjectOfPublication | 119d4edc-08c0-4224-b3ae-0f226bbe224f | |
| relation.isProjectOfPublication.latestForDiscovery | 119d4edc-08c0-4224-b3ae-0f226bbe224f |