A Robust Roll Angle Estimation Algorithm Based on Gradient Descent

Rui Fan, Lujia Wang, Ming Liu, Ioannis Pitas

Abstract: This paper introduces a robust roll angle estimation algorithm, which is developed from our previously published work, where the roll angle was estimated from a dense subpixel disparity map by minimizing a global energy using golden section search algorithm. In this paper, to achieve greater computational efficiency, we utilize gradient descent to optimize the aforementioned global energy. The experimental results illustrate that the presented roll angle estimation method takes fewer iterations to achieve the same precision as the previous method.