@InProceedings{MoraisCampPáduCarc:2005:PaFiPr,
author = "Morais, Erikson Freitas de and Campos, Mario Fernando Montenegro
and P{\'a}dua, Fl{\'a}vio Luis Cardeal and Carceroni, Rodrigo
Lima",
affiliation = "{Departamento de Ci{\^e}ncia da Computa{\c{c}}{\~a}o -
Universidade Federal de Minas Gerais.} and {Instituto DOCTUM}",
title = "Particle filter-based predictive tracking for robust fish
counting",
booktitle = "Proceedings...",
year = "2005",
editor = "Rodrigues, Maria Andr{\'e}ia Formico and Frery, Alejandro
C{\'e}sar",
organization = "Brazilian Symposium on Computer Graphics and Image Processing, 18.
(SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
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%.",
conference-location = "Natal, RN, Brazil",
conference-year = "9-12 Oct. 2005",
doi = "10.1109/SIBGRAPI.2005.36",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2005.36",
language = "en",
ibi = "6qtX3pFwXQZeBBx/GJNM9",
url = "http://urlib.net/ibi/6qtX3pFwXQZeBBx/GJNM9",
targetfile = "paduaf_fishcounting.pdf",
urlaccessdate = "2024, Apr. 28"
}