Multi-level Random Sample Consensus Method for Improving Structured Light Vision Systems

Abstract

The paper proposes a structured light vision system equipped with multi-cameras and multi-laser emitters for object height measurement or 3D reconstruction. The proposed method offers a better accuracy performance over a single camera system. To tackle the intersections produced by laser emitters in the projected image plane, we propose a multi-level random sample consensus (MLRANSAC) algorithm to separate the intersection points instead of using the traditional methods such as time division and color division techniques. Our experiments demonstrate that the MLRANSAC algorithm can perform effectively.