Description

Optical flow estimates a dense 2D velocity field (u, v) from consecutive image frames, classically through brightness-constancy assumptions (Lucas-Kanade, Horn-Schunck) and increasingly via deep networks (FlowNet, RAFT). In crowd modelling it is the camera-domain analogue of crowd-flow-estimation and is the standard ground-truth source for evaluating CSI-derived flow fields on overlapping camera-CSI deployments.

When it's used

  • Camera-based crowd-flow ground truth
  • Evaluation reference for CSI / radar flow estimation
  • Integration into hybrid camera-RF crowd pipelines

Limitations

  • Requires line-of-sight cameras; useless on its own indoors
  • Aperture problem on textureless areas
  • Computational cost of dense flow at high resolution

Source Papers

  • sindagi2018_e579 — optical flow in crowd density / counting
  • sreenu2019_6f76 — optical flow in crowd-analysis review
  • bendalibraham2021_476e — optical flow in crowd analytics

5 vault papers use this method

Titles and DOIs only — no abstracts, no analyses.

  • Crowd monitoring using image processing 1995 DOI ↗
  • Recent trends in crowd analysis: A review 2021 DOI ↗
  • Spatio-Temporal Modeling for Abnormal Behaviour Detection in Crowd Scenes 2026 DOI ↗
  • Physics of Human Crowds 2023 DOI ↗
  • Intelligent video surveillance: a review through deep learning techniques for crowd analysis 2019 DOI ↗