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（Animal Ecology）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制约了生态学研究的广度与范畴，生态学家常借助图像采集手段以提升时空维度上的数据采集效率，但此类图像的处理能力仍为研究瓶颈。 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。该技术通过色彩、形状、纹理等图像特征推导并解析图像内容。 3. 本文对生态计算机视觉（ecological computer vision）进行简要概述，阐明其面向动物生态学的目标、工具与应用场景。 4. 本文梳理了187项已公开的计算机视觉应用案例，并将相关研究文献划分为生态描述、计数与身份识别三类任务。 5. 本文还探讨了加强生态学家与计算机科学家跨领域协作的建议，并点明了自动化图像分析未来的发展方向。