%0 Conference Paper %1 EI2019 %A Jörissen, S. %A Bleier, M. %A Nüchter, A. %B Proceedings of the IS&T International Symposium on Electronic Imaging Science and Technology %C San Francisco, CA, USA %D 2019 %I Society for Imaging Science and Technology %K myown %P 353-1--353-8 %R 10.2352/ISSN.2470-1173.2019.4.PMII-353 %T Self-calibrated Surface Acquisition for Integrated Positioning Verification in Medical Applications %U https://robotik.informatik.uni-wuerzburg.de/telematics/download/ei2019.pdf %X This paper presents a novel approach for a position verification system in medical applications. By replacing the already existing cross line laser projectors with galvo- or MEMS-based projectors and utilizing the surveillance cameras, a self-calibration of the system is performed and surface acquisition for positioning verification is demonstrated. The functionality is shown by analyzing the radii of calibration spheres and determining the quality of the captured surface with respect to a reference model. The paper focuses on the demonstration with one pair of camera and projector but can also be extended to a multi-camera-projector system, as present in treatment rooms. Compared to other systems, this approach does not need external hardware and is thus space and cost efficient.

@inproceedings{EI2019, abstract = {This paper presents a novel approach for a position verification system in medical applications. By replacing the already existing cross line laser projectors with galvo- or MEMS-based projectors and utilizing the surveillance cameras, a self-calibration of the system is performed and surface acquisition for positioning verification is demonstrated. The functionality is shown by analyzing the radii of calibration spheres and determining the quality of the captured surface with respect to a reference model. The paper focuses on the demonstration with one pair of camera and projector but can also be extended to a multi-camera-projector system, as present in treatment rooms. Compared to other systems, this approach does not need external hardware and is thus space and cost efficient.}, added-at = {2019-02-07T10:41:11.000+0100}, address = {San Francisco, CA, USA}, author = {J{\"o}rissen, S. and Bleier, M. and N{\"u}chter, A.}, biburl = {https://www.bibsonomy.org/bibtex/247789ab91be87db395734685bddcbc58/nuechter76}, booktitle = {Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology}, doi = {10.2352/ISSN.2470-1173.2019.4.PMII-353}, interhash = {c316d5f98f814c2cf6d59d0fa00a3d7b}, intrahash = {47789ab91be87db395734685bddcbc58}, keywords = {myown}, month = {January}, pages = {353-1--353-8}, publisher = {Society for Imaging Science and Technology}, series = {Electronic Imaging}, timestamp = {2019-02-07T10:41:11.000+0100}, title = {{Self-calibrated Surface Acquisition for Integrated Positioning Verification in Medical Applications}}, url = {https://robotik.informatik.uni-wuerzburg.de/telematics/download/ei2019.pdf}, year = 2019 }