# A Robust Roll Angle Estimation Algorithm Based on Gradient Descent

## TL;DR

This paper introduces a more efficient roll angle estimation algorithm using gradient descent to optimize a global energy function, reducing iterations while maintaining accuracy.

## Contribution

It replaces the golden section search with gradient descent for faster, more computationally efficient roll angle estimation from disparity maps.

## Key findings

- Fewer iterations needed for the same precision.
- Maintains accuracy comparable to previous methods.
- Improved computational efficiency.

## Abstract

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.