Measurement performance and comparison using optical vision systems

Abstract

The use of optical 3D shape measurement devices are rapidly gaining importance and allow to build models of real 3D objects efficiently. Unfortunately, many current sensing technologies have noise levels of the order of centimeter when measuring from 1-2 meters away. The 3D shape and texture can be obtained from image sequences acquired with a freely moving camera. This approach measures the image displacement from the corresponding feature points in multiple images of the same scene, taken from different views. Although the camera parameters can be estimated from the image sequence, the accuracy can be improved using a calibrated camera. The use of active vision techniques can also be used to improve accuracy of the point correspondence. Among them it is possible to mention the structured light technique. The introduction of active illumination aims to simplify the surface reconstruction problem and provides high accuracy reconstruction by creating a point cloud which represents the shape of the scanned object. The structured light technique projects large patterns onto the scene using a video projector, and observe deformations of the patterns in a camera to infer the depth. Moreover, for static objects, the accuracy can be substantially increased by the use of pattern sequences. To capture reliable data it is possible to use the binary coding to scan a static object.