Paper
6 September 2019 Reconstruction of 3D deformable objects using a single Kinect sensor
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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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marcelo Luis Ruiz-Rodriguez and Vitaly Kober "Reconstruction of 3D deformable objects using a single Kinect sensor", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 1113725 (6 September 2019); https://doi.org/10.1117/12.2528526
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Cited by 1 scholarly publication.
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KEYWORDS
Sensors

Clouds

3D modeling

Reconstruction algorithms

Detection and tracking algorithms

Feature extraction

Image registration

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