High-resolution (5MP+) stereo vision systems are essential for advancing robotic capabilities, enabling operation over longer ranges and generating significantly denser and accurate 3D point clouds. However, realizing the full potential of high-angular-resolution sensors requires a commensurately higher level of calibration accuracy and faster processing -- requirements often unmet by conventional methods. This study addresses that critical gap by processing 5MP camera imagery using a novel, advanced frame-to-frame calibration and stereo matching methodology designed to achieve both high accuracy and speed. Furthermore, we introduce a new approach to evaluate real-time performance by comparing real-time disparity maps with ground-truth disparity maps derived from more computationally intensive stereo matching algorithms. Crucially, the research demonstrates that high-pixel-count cameras yield high-quality point clouds only through the implementation of high-accuracy calibration.

翻译：高分辨率（500万像素以上）立体视觉系统对于提升机器人能力至关重要，能够支持更远距离的操作并生成显著更密集且精确的三维点云。然而，要充分发挥高角分辨率传感器的全部潜力，需要相应更高水平的校准精度与更快的处理速度——这些要求往往是传统方法无法满足的。本研究通过采用一种新颖先进的帧间校准与立体匹配方法处理500万像素相机图像，旨在同时实现高精度与高速度，从而弥补这一关键空白。此外，我们提出了一种通过将实时视差图与基于计算量更大的立体匹配算法得到的真实视差图进行比较，来评估实时性能的新方法。至关重要的是，本研究表明，只有通过实施高精度校准，高像素数相机才能生成高质量的点云。