论文标题
牛健康视频分析的牛结构模型
A cow structural model for video analytics of cow health
论文作者
论文摘要
在牲畜种植中，动物健康直接影响生产力。对于奶牛，可以根据视觉外观和运动来评估许多健康状况。但是，手动评估商业农场中的每头母牛都是昂贵且不切实际的。本文介绍了一个视频分析系统，该系统会自动从捕获的视频序列中检测牛结构。侧视牛结构模型旨在描述牛的关节（关键点）的空间位置，我们使用深度学习来开发一个系统，以自动从视频中提取结构模型。提出的检测系统可以在同一框架中检测多个母牛，并在障碍物（栅栏）和照明不良的实际挑战下提供稳健的性能。与其他对象检测方法相比，该系统提供了更好的检测结果，即使它们彼此接近，也可以成功地隔离每个母牛的关键。
In livestock farming, animal health directly influences productivity. For dairy cows, many health conditions can be evaluated by trained observers based on visual appearance and movement. However, to manually evaluate every cow in a commercial farm is expensive and impractical. This paper introduces a video-analytic system which automatically detects the cow structure from captured video sequences. A side-view cow structural model is designed to describe the spatial positions of the joints (keypoints) of the cow, and we develop a system using deep learning to automatically extract the structural model from videos. The proposed detection system can detect multiple cows in the same frame and provide robust performance under practical challenges like obstacles (fences) and poor illumination. Compared to other object detection methods, this system provides better detection results and successfully isolates the keypoints of each cow even when they are close to each other.
