论文标题

珊瑚礁图像的自动缝合和提取特征用于水坝的浅滩行为分析

Automated Stitching of Coral Reef Images and Extraction of Features for Damselfish Shoaling Behavior Analysis

论文作者

Pineda, Riza Rae, Peñas, Kristofer delas, Manogan, Dana

论文摘要

动物的行为分析涉及观察到环境中各种生物之间种内和种间相互作用。集体行为,例如在农场动物中放牧,鸟类群,鱼类的浅滩和教育提供有关其在集体生存,健身,生殖模式,群体决策以及在动物流行病学中的影响的信息。在海洋伦理学中,对教育物种行为模式的调查可以在海洋资源计划和管理中提供补充信息。目前,虽然在热带水域中流行,但虽然虽然在热带水域中流行,却没有足够的既定基本行为信息。这限制了珊瑚礁经理有效地计划保护珊瑚礁的压力和灾难反应。野外捕获的视觉海洋数据稀缺,容易出现多种场景变化,主要是由运动和自然环境变化引起的。这项研究收集的DAMELSIS视频展示了由摄像机过程中不稳定的相机动作引起的几种场景扭曲。为了有效地分析通过在野外捕获数据所带来的问题的有效分析行为,我们提出了一个预处理系统,该系统利用颜色校正和图像缝合技术,并提取行为特征以进行手动分析。

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, primarily caused by motion and changes in the natural environment. The gathered videos of damselfish by this research exhibit several scene distortions caused by erratic camera motions during acquisition. To effectively analyze shoaling behavior given the issues posed by capturing data in the wild, we propose a pre-processing system that utilizes color correction and image stitching techniques and extracts behavior features for manual analysis.

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