Height estimation from monocular image sequences using dynamic programming with explicit occlusions

In this study, the authors propose a novel algorithm to estimate the heights of objects from monocular aerial images taken from mobile platforms such as unmanned aerial vehicles and small airplanes. Sequential images captured by a single camera mounted on a mobile platform contain 3D information of objects. In this study, the authors propose to use illumination normalisation to reduce illumination variations and to use at least two objects with known distances to accurately estimate the camera focal length. The authors also propose a novel stereo matching algorithm using dynamic programming with explicit occlusion modelling to recover depth information in occluded regions and to preserve depth discontinuity. As a result, the authors are able to reliably estimate the heights of objects in or close to power line corridors. Our experiments show that the proposed algorithm can estimate the heights of trees and power poles from aerial images with average errors of 1.8 and 1.1 m, respectively, when the flight height is in the range between 230 and 280 m above ground level.