论文标题
深度学习的运动捕获入门：原理，陷阱和观点
A Primer on Motion Capture with Deep Learning: Principles, Pitfalls and Perspectives
论文作者
论文摘要
从视频中提取行为测量值是一个严重的计算问题，从而使其从视频中提取出来。深度学习的最新进展已直接从视频中预测了姿势，这很快就更广泛地影响了神经科学和生物学。在此底漆中，我们通过深度学习回顾了运动捕获的萌芽领域。特别是，我们将讨论这些新颖算法的原理，强调它们的潜力以及实验者的陷阱，并瞥见未来。
Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem. Recent advances in deep learning have tremendously advanced predicting posture from videos directly, which quickly impacted neuroscience and biology more broadly. In this primer we review the budding field of motion capture with deep learning. In particular, we will discuss the principles of those novel algorithms, highlight their potential as well as pitfalls for experimentalists, and provide a glimpse into the future.
