Fisheye Stereo Vision: Depth and Range Error

2026-02-03

AI Summary

This study addresses the challenge of accurately modeling depth and distance measurement errors in fisheye stereo vision systems under large field-of-view conditions. For the first time, an analytical error model is established that explicitly accounts for large incidence angles in observation geometry. By integrating the projection characteristics of fisheye lenses with geometric optics modeling and error propagation analysis, the authors derive explicit expressions for depth and distance errors as functions of object distance. The resulting model significantly enhances the theoretical accuracy of error prediction at wide viewing angles, thereby providing a robust theoretical foundation for the design and optimization of high-precision fisheye stereo vision systems.

Technology Category

• Computer Vision: Scene Analysis & Understanding
• Intelligent Robots: State Estimation
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

This study derives analytical expressions for the depth and range error of fisheye stereo vision systems as a function of object distance, specifically accounting for accuracy at large angles.

Problem

• fisheye stereo vision
• depth error
• range error
• large angles
• object distance

Innovation

• fisheye stereo vision
• depth error
• range error
• analytical expression
• large-angle accuracy