Data from: A computer vision for animal ecology

1. A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck.
2. Computer vision can greatly increase the efficiency, repeatability, and accuracy of image review. Computer vision uses image features, such as color, shape, and texture to infer image content.
3. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology.
4. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting, and identity tasks.
5. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis.

1. 动物生态学的核心目标之一是在自然环境中观测物种。数据采集的成本与挑战往往限制了生态学研究的广度与范畴。生态学家常通过图像采集来强化时空维度上的数据采集能力，但此类图像的处理能力仍是当前的瓶颈。
2. 计算机视觉（Computer vision）可大幅提升图像审阅的效率、可重复性与准确性。计算机视觉通过色彩、形状、纹理等图像特征来推断图像的具体内容。
3. 本文针对生态计算机视觉（ecological computer vision）撰写了简要入门指南，旨在阐明其面向动物生态学的目标、工具与应用方向。
4. 本文梳理了187项已公开的计算机视觉应用案例，并将相关文献划分为生态描述、计数与识别三类任务。
5. 本文还就加强生态学家与计算机科学家之间的协作提出了建议，并指明了自动化图像分析领域未来的发展重点。