Pubblicazione scientifica

Fish activity tracking and species identification in underwater video

FILONE TECNOLOGICO	TEMA
produzione e cattura

RIASSUNTO

In this paper we propose an automatic marine life monitoring system. First task in the monitoring process is to detect underwater moving objects as fishes. Second Task is to identify the species of the detected fish. Third task is to track the detected fish to avoid multiple counting and record their activities. Detection is performed using GMM based background subtraction method, classification is performed using Pyramid Histogram Of visual Words (PHOW) features with SVM classifier and finally identified fishes are tracked using “Kalman Filter”. This experiment is performed using data-set from the CLEF 2015. The proposed system can detect and track fishes with 48.94 percent accuracy in videos, and it can identify fishes in high resolution still image with 91.7 percent accuracy where as in the low quality video fishes are detected with 40.1 percent accuracy.

DATA

Data di pubblicazione: 01/05/2016

AUTORI

EKRAM HOSSAIN
S M SHAIFUL ALAM
AMIN AHSAN ALI
M ASHRAFUL AMIN

ENTE DI AFFERENZA

COMPUTER SCIENCE & ENG DHAKA UNIV BANGLADESH
COMPUTER VISION & CYBERNETICS GROUP CSE INDEPENDENT UNIV BANGLADESH

RIVISTA

2016 5th International Conference on Informatics, Electronics and Vision (ICIEV) (Page(s): 62-66)

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