Fusing Depth and Silhouette for Scanning Transparent Object with RGB-D Sensor

Abstract

3D reconstruction based on structured light or laser scan has been widely used in industrial measurement, robot navigation, and virtual reality. However, most modern range sensors fail to scan transparent objects and some other special materials, of which the surface cannot reflect back the accurate depth because of the absorption and refraction of light. In this paper, we fuse the depth and silhouette information from an RGB-D sensor (Kinect v1) to recover the lost surface of transparent objects. Our system is divided into two parts. First, we utilize the zero and wrong depth led by transparent materials from multiple views to search for the 3D region which contains the transparent object. Then, based on shape from silhouette technology, we recover the 3D model by visual hull within these noisy regions. Joint Grabcut segmentation is operated on multiple color images to extract the silhouette. The initial constraint for Grabcut is automatically determined. Experiments validate that our approach can improve the 3D model of transparent object in real-world scene. Our system is time-saving, robust, and without any interactive operation throughout the process.