Visual Analytics for Cheetah Behaviour Analysis

Karsten Klein, Sabrina Jaeger, J. Melzheimer, B. Wachter, H. Hofer, Artur Baltabayev, F. Schreiber
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引用次数: 2

Abstract

Recent advances in tracking technology allow biologists to collect large amounts of movement data for a variety of species. Analysis of the collected data supports research on animal behaviour, influence of impact factors such as climate change and human intervention, as well as conservation programs. Analysis of the movement data is difficult, due to the nature of the research questions and the complexity of the data sets. It requires both automated analysis, e.g. for the detection of behavioural patterns, and human inspection, e.g. for interpretation, inclusion of previous knowledge, and for conclusions on future actions and decision making. We present a concept and implementation for the visual analysis of cheetah movement data in a web-based fashion that allows usage both in the field and in office environments.
猎豹行为分析的视觉分析
跟踪技术的最新进展使生物学家能够收集各种物种的大量运动数据。对收集到的数据的分析支持对动物行为、气候变化和人类干预等影响因素的影响以及保护计划的研究。由于研究问题的性质和数据集的复杂性,运动数据的分析是困难的。它既需要自动分析,例如用于检测行为模式,也需要人工检查,例如用于解释,包含先前的知识,以及关于未来行动和决策的结论。我们提出了一个概念和实现,以基于web的方式对猎豹运动数据进行可视化分析,允许在现场和办公环境中使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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