Publication
3D object reconstruction from Swissranger sensor data using a spring-mass model
Conference Article
Conference
International Conference on Computer Vision Theory and Applications (VISAPP)
Edition
4th
Pages
368-372
Doc link
http://visapp.visigrapp.org/VISAPP2009/
File
Abstract
We register close-range depth images of objects using a Swissranger sensor and apply a spring-mass model for 3D object reconstruction. The Swissranger sensor delivers depth images in real time which have, compared with other types of sensors, such as laser scanners, a lower resolution and are afflicted with larger uncertainties. To reduce noise and remove outliers in the data, we treat the point cloud as a system of interacting masses connected via elastic forces. We investigate two models, one with and one without a surface-topology preserving interaction strength. The algorithm is applied to synthetic and real Swissranger sensor data, demonstrating the feasibility of the approach. This method represents a preliminary step before fitting higher-level surface descriptors to the data, which will be required to define object-action complexes (OACS) for robot applications.
Categories
computer vision.
Author keywords
Swissranger sensor, 3D reconstruction, spring-mass model
Scientific reference
B. Dellen, G. Alenyà, S. Foix and C. Torras. 3D object reconstruction from Swissranger sensor data using a spring-mass model, 4th International Conference on Computer Vision Theory and Applications, 2009, Lisboa, pp. 368-372, 2009, INSTICC Press.
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