Abstract
This paper deals with the 3D reconstruction problem for dynamic non-rigid objects with a single RGB-D sensor. It is a challenging task as we consider the almost inevitable accumulation error issue in some previous sequential fusion methods and also the possible failure of surface tracking in a long sequence. Therefore, we propose a global non-rigid registration framework and tackle the drifting problem via an explicit loop closure. Our novel scheme starts with a fusion step to get multiple partial scans from the input sequence, followed by a pairwise non-rigid registration and loop detection step to obtain correspondences between neighboring partial pieces and those pieces that form a loop. Then, we perform a global registration procedure to align all those pieces together into a consistent canonical space as guided by those matches that we have established. Finally, our proposed model-update step helps fixing potential misalignments that still exist after the global registration. Both geometric and appearance constraints are enforced during our alignment; therefore, we are able to get the recovered model with accurate geometry as well as high fidelity color maps for the mesh. Experiments on both synthetic and various real datasets have demonstrated the capability of our approach to reconstruct complete and watertight deformable objects.
Document Type
Article
Publication Date
3-16-2018
Digital Object Identifier (DOI)
https://doi.org/10.3390/s18030886
Funding Information
This work was supported by the US NSF (IIS-1231545, IIP-1543172), US Army Research grant W911NF-14-1-0437, the National Natural Science Foundation of China (No. 51475373, 61603302, 51375390, 61332017), the Key Industrial Innovation Chain of Shaanxi Province Industrial Area (2016KTZDGY06-01, 2015KTZDGY04-01), the Natural Science Foundation of Shaanxi (No. 2016JQ6009), and the “111 Project” (No.B13044).
Repository Citation
Wang, Sen; Zuo, Xinxin; Du, Chao; Wang, Runxiao; Zheng, Jiangbin; and Yang, Ruigang, "Dynamic Non-Rigid Objects Reconstruction with a Single RGB-D Sensor" (2018). Computer Science Faculty Publications. 16.
https://uknowledge.uky.edu/cs_facpub/16
Notes/Citation Information
Published in Sensors, v. 18, issue 3, p. 1-18.
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).