3D object reconstruction from Swissranger sensor data using a spring-mass model
Document typePart of book or chapter of book
PublisherINSTICC Press. Institute for Systems and Technologies of Information, Control and Communication
Rights accessRestricted access - publisher's policy
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.
CitationDellen, B. [et al.]. 3D object reconstruction from Swissranger sensor data using a spring-mass model. A: "Computer Vision, Theory and Applications". INSTICC Press. Institute for Systems and Technologies of Information, Control and Communication, 2009, p. 368-372.