A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives

Neuron. 2020 Oct 14;108(1):44-65. doi: 10.1016/j.neuron.2020.09.017.

Abstract

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 our ability to predict posture directly from videos, which has 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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Video-Audio Media

MeSH terms

  • Algorithms
  • Animals
  • Deep Learning*
  • Humans
  • Motion
  • Motor Activity
  • Movement*
  • Neural Networks, Computer
  • Video Recording*