Authors: Maria L. Hänel; Stefan Kuhn; Dominik Henrich; Lars Grüne; Jürgen Pannek
Addresses: Chair of Applied Computer Science III, University of Bayreuth, D-95445 Bayreuth, Germany. ' Chair of Applied Computer Science III, University of Bayreuth, D-95445 Bayreuth, Germany. ' Chair of Applied Computer Science III, University of Bayreuth, D-95445 Bayreuth, Germany. ' Chair of Applied Mathematics, University of Bayreuth, D-95445 Bayreuth, Germany. ' Faculty of Aeronautics, University of the Federal Armed Forces Munich, 85577 Munich/Neubiberg, Germany
Abstract: In modern production facilities industrial robots and humans are supposed to share a common working area. To avoid collisions, the distances between objects need to be measured conservatively, which can be done by a camera network. To estimate these distances, unmodelled objects, e.g. an interacting human, need to be modelled and distinguished from pre-modelled objects, like workbenches or robots, by image processing such as the background subtraction method. The quality of such an approach massively depends on the position and orientation of each camera. Of particular interest in this context is the error minimisation of the above mentioned distance determined by image processing. Here, we formulate this minimisation as an abstract optimisation problem. Moreover, we state various aspects on the implementation, e.g. reasons for the selection of a suitable optimisation method, analyse the complexity of the proposed method and present a basic version used for extensive experiments.
Keywords: close range photogrammetry; optimisation; camera networks; camera placement; error minimisation; obstacles; distance measurement; optimal placement; static obstacles; dynamic obstacles; optimal image processing; camera position; camera orientation; camera pose; sensor networks; occlusions.
International Journal of Sensor Networks, 2012 Vol.12 No.1, pp.25 - 36
Received: 04 May 2011
Accepted: 10 Feb 2012
Published online: 08 Jul 2012 *