Identity statement area | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Identifier | 6qtX3pFwXQZeBBx/GJNM9 |
Repository | sid.inpe.br/banon/2005/07.12.19.31 |
Last Update | 2005:07.13.03.00.00 administrator |
Metadata | sid.inpe.br/banon/2005/07.12.19.31.20 |
Metadata Last Update | 2020:02.19.03.19.12 administrator |
Citation Key | MoraisCampPáduCarc:2005:PaFiPr |
Title | Particle filter-based predictive tracking for robust fish counting  |
Format | On-line |
Year | 2005 |
Access Date | 2021, Jan. 25 |
Number of Files | 1 |
Size | 541 KiB |
Context area | |
Author | 1 Morais, Erikson Freitas de 2 Campos, Mario Fernando Montenegro 3 Pádua, Flávio Luis Cardeal 4 Carceroni, Rodrigo Lima |
Affiliation | 1 Departamento de Ciência da Computação - Universidade Federal de Minas Gerais. 2 Instituto DOCTUM |
Editor | Rodrigues, Maria Andréia Formico Frery, Alejandro César |
e-Mail Address | cardeal@dcc.ufmg.br |
Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 18 (SIBGRAPI) |
Conference Location | Natal |
Date | 9-12 Oct. 2005 |
Book Title | Proceedings |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Tertiary Type | Full Paper |
History | 2008-07-17 14:10:59 :: cardeal -> banon :: 2008-08-26 15:17:01 :: banon -> administrator :: 2009-08-13 20:37:48 :: administrator -> banon :: 2010-08-28 20:01:18 :: banon -> administrator :: 2020-02-19 03:19:12 :: administrator -> :: 2005 |
Content and structure area | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | tracking, particle filter, fish counting, BraMBle. |
Abstract | In this paper we study the use of computer vision techniques for for underwater visual tracking and counting of fishes in vivo. The methodology is based on the application of a Bayesian filtering technique that enables tracking of objects whose number may vary over time. Unlike existing fish-counting methods, this approach provides adequate means for the acquisition of relevant information about characteristics of different fish species such as swimming ability, time of migration and peak flow rates. The system is also able to estimate fish trajectories over time, which can be further used to study their behaviors when swimming in regions of interest. Our experiments demonstrate that the proposed method can operate reliably under severe environmental changes (e.g. variations in water turbidity) and handle problems such as occlusions or large inter-frame motions. The proposed approach was successfully validated with real-world video streams, achieving overall accuracy as high as 81%. |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
Conditions of access and use area | |
data URL | http://urlib.net/rep/6qtX3pFwXQZeBBx/GJNM9 |
zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/GJNM9 |
Language | en |
Target File | paduaf_fishcounting.pdf |
User Group | cardeal administrator |
Visibility | shown |
Allied materials area | |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
Notes area | |
Empty Fields | accessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark mirrorrepository nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
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