Dive Deeper into Rectifying Homography for Stereo Camera Online Self-Calibration

TL;DR

This paper presents a novel online self-calibration algorithm for stereo cameras that leverages rectifying homography, providing improved accuracy and robustness in extrinsic parameter estimation from single image pairs or stereo video sequences.

Contribution

The paper introduces a new stereo camera self-calibration method based on rectifying homography, with a global optimum solution and four novel evaluation metrics for robustness and accuracy.

Findings

Outperforms baseline algorithms in indoor and outdoor tests

Effective for single image pair and stereo video sequences

Validated through extensive experiments

Abstract

Accurate estimation of stereo camera extrinsic parameters is the key to guarantee the performance of stereo matching algorithms. In prior arts, the online self-calibration of stereo cameras has commonly been formulated as a specialized visual odometry problem, without taking into account the principles of stereo rectification. In this paper, we first delve deeply into the concept of rectifying homography, which serves as the cornerstone for the development of our novel stereo camera online self-calibration algorithm, for cases where only a single pair of images is available. Furthermore, we introduce a simple yet effective solution for global optimum extrinsic parameter estimation in the presence of stereo video sequences. Additionally, we emphasize the impracticality of using three Euler angles and three components in the translation vectors for performance quantification. Instead, we introduce four new evaluation metrics to quantify the robustness and accuracy of extrinsic parameter estimation, applicable to both single-pair and multi-pair cases. Extensive experiments conducted across indoor and outdoor environments using various experimental setups validate the effectiveness of our proposed algorithm. The comprehensive evaluation results demonstrate its superior performance in comparison to the baseline algorithm. Our source code, demo video, and supplement are publicly available at mias.group/StereoCalibrator.