Detailed modeling and calibration of a Time-of-Flight camera

In this paper we propose a physically motivated sensor model of Time-of-Flight cameras. We provide methods to calibrate our proposed model and compensate all modeled effects. This enables us to reliably detect and filter out inconsistent measurements and to record high dynamic range (HDR) images. We believe that HDR images have a significant benefit especially for mapping narrow-spaced environments as in urban search and rescue. We provide methods to invert our model in real-time and gain significantly higher precision than using the vendor-provided sensor driver. In contrast to previously published purely phenomenological calibration methods our model is physically motivated and thus better captures the structure of the different effects involved.