3D object reconstruction from Swissranger sensor data using a spring-mass model

Presentado al International Conference on Computer Vision Theory and Applications (VISAPP/2009) celebrado en Lisboa (Portugal).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.This work was supported by projects: 'Perception, action & cognition through learning of object-action complexes.' (4915), 'Grup de recerca consolidat - Grup de Robòtica' (4810). This work has received support from the BMBF funded BCCN Göttingen, the EU Project PACOPLUS under contract FPG-2004-IST-4-027657, and the Generalitat de Catalunya through the Robotics group. G. Alenyà was supported by the CSIC under a Jae-Doc Fellowship.Peer Reviewe