%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2020/09.29.03.25
%2 sid.inpe.br/sibgrapi/2020/09.29.03.25.18
%@doi 10.1109/SIBGRAPI51738.2020.00026
%T Online frame-to-model pipeline to 3D reconstruction with depth cameras using RGB-D information
%D 2020
%A Dornelles, Thiago,
%A Jung, Claudio,
%@affiliation Institute of Informatics - Federal University of Rio Grande do Sul
%@affiliation Institute of Informatics - Federal University of Rio Grande do Sul
%E Musse, Soraia Raupp,
%E Cesar Junior, Roberto Marcondes,
%E Pelechano, Nuria,
%E Wang, Zhangyang (Atlas),
%B Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)
%C Porto de Galinhas (virtual)
%8 7-10 Nov. 2020
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K 3D Reconstruction, Visual Odometry, RGBD Cameras, Frame-to-Model.
%X This work presents an online pipeline for incremental 3D reconstruction and 6-DoF camera pose estimation based on colored point clouds captured by consumer RGB-D cameras. The proposed approach combines geometric matching provided by the point cloud with photometric matching provided by the color sensor through an adaptive weighting scheme that avoids eventual misalignment errors between RGB and depth data. Our experimental results indicate that the 3D reconstructions achieved by the proposed scheme are visually better or similar than a competitive approach.
%@language en
%3 SIBGRAPI IEEE APPROVED.pdf