High frame rate for 3D time-of-flight cameras by dynamic sensor calibration (bibtex)
by Mirko Schmidt, Klaus Zimmermann, Bernd Jähne
Abstract:
3D Time-of-Flight cameras are able to deliver robust depth maps of dynamic scenes. The frame rate, however, is limited because today's systems utilizing two-tap sensors need to acquire the required raw images in multiple instances in order to compute one depth map. These multiple raw images allow canceling out systematic errors introduced by asymmetries in the two taps, which otherwise would distort the reconstructed depth map. This work presents a method to implicitly calibrate these asymmetries of multi-tap 3D Time-of-Flight sensors. The calibration data are gathered from arbitrary live acquisitions possibly in real-time. The proposed correction of raw data supersedes the commonly used averaging technique. Thus it is possible to compute multiple depth maps from a single set of raw images. This increases the frame rate by at least a factor of two. The method is verified using real camera data and is evaluated quantitatively.
Reference:
High frame rate for 3D time-of-flight cameras by dynamic sensor calibration (Mirko Schmidt, Klaus Zimmermann, Bernd Jähne), In Proceedings IEEE International Conference on Computational Photography (ICCP), 2011.
Bibtex Entry:
@InProceedings{schmidt2011a,
  Title                    = {High frame rate for {3D} time-of-flight cameras by dynamic sensor calibration},
  Author                   = {Schmidt, Mirko and Zimmermann, Klaus and Jähne, Bernd},
  Booktitle                = {Proceedings IEEE International Conference on Computational Photography (ICCP)},
  Year                     = {2011},
  Pages                    = {1--8},

  __markedentry            = {[mischmidt]},
  Abstract                 = {3D Time-of-Flight cameras are able to deliver robust depth maps of dynamic scenes. The frame rate, however, is limited because today's systems utilizing two-tap sensors need to acquire the required raw images in multiple instances in order to compute one depth map. These multiple raw images allow canceling out systematic errors introduced by asymmetries in the two taps, which otherwise would distort the reconstructed depth map. This work presents a method to implicitly calibrate these asymmetries of multi-tap 3D Time-of-Flight sensors. The calibration data are gathered from arbitrary live acquisitions possibly in real-time. The proposed correction of raw data supersedes the commonly used averaging technique. Thus it is possible to compute multiple depth maps from a single set of raw images. This increases the frame rate by at least a factor of two. The method is verified using real camera data and is evaluated quantitatively.},
  Access                   = {1},
  Doi                      = {10.1109/ICCPHOT.2011.5753121},
  File                     = {http:http\://hci.iwr.uni-heidelberg.de/publications/dip/2011/Schmidt_ICCP2011.pdf:PDF},
  Groupid                  = {dip},
  Owner                    = {mischmidt},
  Peer                     = {yes},
  Timestamp                = {2011.05.03}
}