A Robust Roll Angle Estimation Algorithm Based on Gradient Descent

Rui Fan, Lujia Wang, Ming Liu, Ioannis Pitas

This paper presents a robust roll angle estimation algorithm, which is developed from our previously published work, where the roll angle was estimated from a dense 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 proposed roll angle estimation algorithm takes fewer iterations to achieve the same precision as the previous method.

Knowledge Graph



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