Investigation of moving objects through atmospheric turbulence from a non-stationary platform

TL;DR

This paper presents a method to extract and analyze moving objects in scenes affected by atmospheric turbulence from a moving camera, combining optical flow, motion modeling, and flow decomposition.

Contribution

It introduces a novel approach that compensates for camera motion and separates atmospheric turbulence from object motion using flow decomposition techniques.

Findings

Effective separation of turbulence and object motion

Open source sequences and code provided

Improved detection and tracking accuracy

Abstract

In this work, we extract the optical flow field corresponding to moving objects from an image sequence of a scene impacted by atmospheric turbulence \emph{and} captured from a moving camera. Our procedure first computes the optical flow field and creates a motion model to compensate for the flow field induced by camera motion. After subtracting the motion model from the optical flow, we proceed with our previous work, Gilles et al~\cite{gilles2018detection}, where a spatial-temporal cartoon+texture inspired decomposition is performed on the motion-compensated flow field in order to separate flows corresponding to atmospheric turbulence and object motion. Finally, the geometric component is processed with the detection and tracking method and is compared against a ground truth. All of the sequences and code used in this work are open source and are available by contacting the authors.