High-Definition 5MP Stereo Vision Sensing for Robotics
Leaf Jiang, Matthew Holzel, Bernhard Kaplan, Hsiou-Yuan Liu, Sabyasachi Paul, Karen Rankin, and Piotr Swierczynski

TL;DR
This paper presents a novel calibration and stereo matching method for 5MP stereo vision systems, enabling high-accuracy, real-time 3D sensing crucial for advanced robotic applications.
Contribution
It introduces an advanced calibration and stereo matching approach tailored for high-resolution cameras, improving accuracy and speed for robotic 3D perception.
Findings
High-resolution cameras produce better 3D point clouds with proper calibration.
The proposed method achieves real-time disparity map computation.
Calibration accuracy is critical for high-quality 3D sensing.
Abstract
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…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Advanced Vision and Imaging · Optical measurement and interference techniques
