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Reconstruction of 3D deformable objects using a single Kinect sensor
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Paper Abstract

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.

Paper Details

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
Show Author Affiliations
Vitaly Kober, CICESE (Mexico)
Chelyabinsk State Univ. (Russian Federation)


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

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