COVARIANCE BASED FISH TRACKING IN REAL-LIFE UNDERWATER ENVIRONMENT

Concetto Spampinato, Simone Palazzo, Daniela Giordano, Isaak Kavasidis, Fang-Pang Lin, Yun-Te Lin

2012

Abstract

In this paper we present a covariance based tracking algorithm for intelligent video analysis to assist marine biologists in understanding the complex marine ecosystem in the Ken-Ding sub-tropical coral reef in Taiwan by processing underwater real-time videos recorded in open ocean. One of the most important aspects of marine biology research is the investigation of fish trajectories to identify events of interest such as fish preying, mating, schooling, etc. This task, of course, requires a reliable tracking algorithm able to deal with 1) the difficulties of following fish that have multiple degrees of freedom and 2) the possible varying conditions of the underwater environment. To accommodate these needs, we have developed a tracking algorithm that exploits covariance representation to describe the object’s appearance and statistical information and also to join different types of features such as location, color intensities, derivatives, etc. The accuracy of the algorithm was evaluated by using hand-labeled ground truth data on 30000 frames belonging to ten different videos, achieving an average performance of about 94%, estimated using multiple ratios that provide indication on how good is a tracking algorithm both globally (e.g. counting objects in a fixed range of time) and locally (e.g. in distinguish occlusions among objects).

Paper Citation

in Harvard Style

Spampinato C., Palazzo S., Giordano D., Kavasidis I., Lin F. and Lin Y. (2012). COVARIANCE BASED FISH TRACKING IN REAL-LIFE UNDERWATER ENVIRONMENT . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 409-414. DOI: 10.5220/0003866604090414

in Bibtex Style

@conference{visapp12,
author={Concetto Spampinato and Simone Palazzo and Daniela Giordano and Isaak Kavasidis and Fang-Pang Lin and Yun-Te Lin},
title={COVARIANCE BASED FISH TRACKING IN REAL-LIFE UNDERWATER ENVIRONMENT},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={409-414},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003866604090414},
isbn={978-989-8565-04-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - COVARIANCE BASED FISH TRACKING IN REAL-LIFE UNDERWATER ENVIRONMENT
SN - 978-989-8565-04-4
AU - Spampinato C.
AU - Palazzo S.
AU - Giordano D.
AU - Kavasidis I.
AU - Lin F.
AU - Lin Y.
PY - 2012
SP - 409
EP - 414
DO - 10.5220/0003866604090414