ロボティクス向け高精細5MPステレオビジョンセンシング
High-Definition 5MP Stereo Vision Sensing for Robotics
5MPカメラ画像に対し高精度なフレーム間キャリブレーションとステレオマッチングを適用し、高密度で正確な3D点群を高速に生成する手法を提案した。
著者: Leaf Jiang, Matthew Holzel, Bernhard Kaplan, Hsiou-Yuan Liu, Sabyasachi Paul, Karen Rankin, Piotr Swierczynski
分類: cs.RO, cs.CV
原文アブストラクト
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.