Improving monocular camera localization for video-based three-dimensional outer ear reconstruction tasks

Abstract

This work addresses challenges related to camera 3D localization while reconstructing a 3D model of an ear. This work explores the potential solution of using a cap, specifically designed not to obstruct the ear, and its efficiency in enhancing the camera localization for structure-from-motion (SfM)-based object reconstruction. The proposed solution is described, and an elaboration of the experimental scenarios used to investigate the background textures is provided; data collection and software tools used in the research are reported. The results show that the proposed method is effective, and using the cap with texture leads to a reduction in the camera localization error. Errors in the 3D location reconstruction of the camera were calculated by comparing cameras localized within typical ear reconstruction situations to those of higher-accuracy reconstructions. The findings also show that caps with sparse dot patterns and a regular knitted patterned winter hat are the preferred patterns. The study provides a contribution to the field of 3D modeling, particularly in the context of creating 3D models of the human ear, and offers a step towards more accurate, reliable, and feasible 3D ear modeling and reconstruction.