Automated Real-time 3D Reconstruction for Indoor Environments Using Monocular Vision

Download or read book Automated Real-time 3D Reconstruction for Indoor Environments Using Monocular Vision written by Samir Shaker and published by . This book was released on 2010 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three-dimensional maps are useful in various applications: from games, to augmented reality, to the development of tour guides of important landmarks such as museums or university campuses. The manual creation of such maps is labor intensive and has therefore justified its automation using robots with range sensors such as lasers or robots with cameras. This thesis presents an automated 3D reconstruction system for indoor environments using only one camera on a mobile robot with an algorithm that runs in real-time. It relies on a vision-based Occupancy Grid SLAM (Simultaneous Localization and Mapping) to detect the ground. The novelty of this work is the method in which 3D information is extracted and fed to SLAM. The ground is first detected by fitting planes to salient features in image segments and by determining the height and orientation of those planes. Then on the height of the ground, 3D virtual rays are cast in a multitude of angles starting from the camera center until they reach the edges of the ground segments in the image. Detection of the ground boundaries is done by continually reprojecting each ray from the 3D world to the 2D image plane. Dense depth information can then be suggested from these rays and input to SLAM. Edge detection and line fitting is then used on the SLAM map to extend walls from those edges until they reach the ceiling. The system produces good quality maps and reduces the high computational cost of dense stereo matching by processing only a sparse set of salient features in real-time. Extensive experiments are conducted inside a lab setting and results prove the success of the system.