3D reconstruction from web harvested images using a forensic quality metric

Abstract

Structure-from-Motion (SfM) algorithms have recently been employed to reconstruct 3D scenes or environments from large sets of unordered images which were harvested from the web. Unfortunately, the accuracy of the reconstruction is significantly affected by the quality and the amount of editing operated on the processed images. Indeed, 3D modelling can significantly benefit from including forensic analysis strategies that are able to reconstruct the processing history of the processed images and select the most reliable pieces of visual information. The current paper presents an SfM strategy that orders the different views/images of the scene in the reconstruction process according to a processing age metric, i.e., a metric parameterizing the amount of processing stages operated on each image. Experimental results show that the proposed solution can improve the estimation accuracy of both 3D points and camera parameters with respect to state-of-the-art solutions.