Detection of Defective Regions in 3D Reconstruction to Support Image Acquisition

Abstract

: To successfully reconstruct a three-dimensional (3D) model from images, it is necessary to make the user aware of whether sufficient data has been obtained. We propose a novel approach to detect defective regions in 3D reconstruction during image acquisition. Our method uses line-based segmentation to segment the acquired images into structural and non-structural regions. Then, using the 3D structures derived from these images, defects detected in the structural region are used to suppress spurious artifacts. Visualization of a defective region in a newly acquired image allows the user to comprehend the reconstruction state and adjust image acquisition. The proposed method was experimentally demonstrated to work successfully in a range of outdoor environments.