Authors:
Christoph Hertzberg
and
Udo Frese
Affiliation:
University of Bremen, Germany
Keyword(s):
Time-of-Flight Camera, Depth Sensor, Sensor Model, Calibration, Robustified Corner Extraction, High Dynamic Range, Lens Scattering.
Related
Ontology
Subjects/Areas/Topics:
Image Processing
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Nonlinear Signals and Systems
;
Optimization Algorithms
;
Robotics and Automation
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
;
Signal Reconstruction
;
System Modeling
;
Vision, Recognition and Reconstruction
Abstract:
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.