| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
| Identifier | 6qtX3pFwXQZeBBx/GJNM9 |
| Repository | sid.inpe.br/banon/2005/07.12.19.31 |
| Last Update | 2005:07.13.03.00.00 (UTC) administrator |
| Metadata Repository | sid.inpe.br/banon/2005/07.12.19.31.20 |
| Metadata Last Update | 2022:06.14.00.12.57 (UTC) administrator |
| DOI | 10.1109/SIBGRAPI.2005.36 |
| Citation Key | MoraisCampPáduCarc:2005:PaFiPr |
| Title | Particle filter-based predictive tracking for robust fish counting  |
| Format | On-line |
| Year | 2005 |
| Access Date | 2024, Apr. 29 |
| Number of Files | 1 |
| Size | 541 KiB |
| 2. Context | |
| 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, RN, Brazil |
| Date | 9-12 Oct. 2005 |
| Publisher | IEEE Computer Society |
| Publisher City | Los Alamitos |
| Book Title | Proceedings |
| Tertiary Type | Full Paper |
| History (UTC) | 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 :: 2022-06-14 00:12:57 :: administrator -> :: 2005 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Version Type | finaldraft |
| 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%. |
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2005 > Particle filter-based predictive... |
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Particle filter-based predictive... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| data URL | http://urlib.net/ibi/6qtX3pFwXQZeBBx/GJNM9 |
| zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/GJNM9 |
| Language | en |
| Target File | paduaf_fishcounting.pdf |
| User Group | cardeal administrator |
| Visibility | shown |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPEW34M/46R3ED5 8JMKD3MGPEW34M/4742MCS |
| Citing Item List | sid.inpe.br/sibgrapi/2022/05.05.04.08 6 |
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
| 6. Notes | |
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume |