Structured light and stereo vision for underwater 3D reconstruction

Abstract

Stereo vision and structured light are compared in a common underwater environment with known dimensions and objects. Two different sensors are mounted on top of a Cartesian robot that moves with a known and programmed trajectory. The resulting point clouds from each sensor are compared in terms of distance from point to point, and measurements in the scanned objects, to determine which sensor is best suited depending on the environment and the survey purpose. The conclusions show that a stereo based reconstruction is best suited for long, high altitude surveys, always depending on having enough texture and light, whereas a structured light reconstruction can be better fitted in a short, close distance approach where accurate dimensions of an object or structure are needed.