Automated Stitching of Coral Reef Images and Extraction of Features for Damselfish Shoaling Behavior Analysis
Riza Rae Pineda, Kristofer delas Pe\~nas, Dana Manogan

TL;DR
This paper presents an automated system for stitching coral reef images and extracting features to analyze damselfish shoaling behavior, addressing challenges of scene distortions in wild marine video data.
Contribution
It introduces a novel pre-processing pipeline combining color correction and image stitching to facilitate behavior analysis in challenging marine environments.
Findings
Effective image stitching compensates for scene distortions.
Extracted features enable manual analysis of damselfish shoaling.
Improved data quality aids reef management strategies.
Abstract
Behavior analysis of animals involves the observation of intraspecific and interspecific interactions among various organisms in the environment. Collective behavior such as herding in farm animals, flocking of birds, and shoaling and schooling of fish provide information on its benefits on collective survival, fitness, reproductive patterns, group decision-making, and effects in animal epidemiology. In marine ethology, the investigation of behavioral patterns in schooling species can provide supplemental information in the planning and management of marine resources. Currently, damselfish species, although prevalent in tropical waters, have no adequate established base behavior information. This limits reef managers in efficiently planning for stress and disaster responses in protecting the reef. Visual marine data captured in the wild are scarce and prone to multiple scene variations,…
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