3D object reconstruction has multiple applications in areas such as medicine, robotics, virtual reality, video games, reverse engineering, human computer interaction among others. This work addresses the following research problem: design of an algorithm for accurate real-time reconstruction of 3D deformable objects using a single Kinect sensor without restricting too much user or camera motion. Prior knowledge of the object shape is not used, allowing a general scanning of the object with free deformations. The reconstruction process consists of the following steps: capture in time of RGB-D information with a Kinect sensor, registration using a modified iterative closest point algorithm, and dynamic construction and refinement of a dense 3D object model. To improve the model quality, segmentation of the desired object from background based on a depth-error analysis is employed. The performance of the algorithm is evaluated using experimentally validated data and compared with state-of-the-art techniques in challenging sequences. The algorithm is implemented on a computer with a graphics processing unit using parallel programming.

Date Published: 6 September 2019
PDF: 14 pages
Proc. SPIE 11137, Applications of Digital Image Processing XLII, 1113725 (6 September 2019); doi: 10.1117/12.2528526

Published in SPIE Proceedings Vol. 11137:
Applications of Digital Image Processing XLII
Andrew G. Tescher; Touradj Ebrahimi, Editor(s)