Publication

Object modeling using a ToF camera under an uncertainty reduction approach

Conference Article

Conference

IEEE International Conference on Robotics and Automation (ICRA)

Edition

2010

Pages

1306-1312

Doc link

http://dx.doi.org/10.1109/ROBOT.2010.5509197

File

Download the digital copy of the doc pdf document

Abstract

Time-of-Flight (ToF) cameras deliver 3D images at 25 fps, offering great potential for developing fast object modeling algorithms. Surprisingly, this potential has not been extensively exploited up to now. A reason for this is that, since the acquired depth images are noisy, most of the available registration algorithms are hardly applicable. A further difficulty is that the transformations between views are in general not accurately known, a circumstance that multi-view object modeling algorithms do not handle properly under noisy conditions. In this work, we take into account both uncertainty sources (in images and camera poses) to generate spatially consistent 3D object models fusing multiple views with a probabilistic approach. We propose a method to compute the covariance of the registration process, and apply an iterative state estimation method to build object models under noisy conditions.

Categories

robots.

Scientific reference

S. Foix, G. Alenyà, J. Andrade-Cetto and C. Torras. Object modeling using a ToF camera under an uncertainty reduction approach, 2010 IEEE International Conference on Robotics and Automation, 2010, Anchorage, AK, USA, pp. 1306-1312.