Statistical analysis of measurement processes for time-of-flight cameras

In recent years, the demand for 3D vision systems has increased in fields such as detection and recognition, motion modelling, 3D environment reconstruction and tracking. This has motivated the development of range image technology, especially Time-of-Flight (TOF) cameras, that provide direct measurement of distance between the camera and the targeted surface. These devices have an advantage over traditional range data sensors due to their capability to provide frame rate range data over a full image array. The quality of the measurement of these sensors depends heavily on signal-to-noise (SNR) of the incoming signal and the subsequent processing algorithms. In phase shift TOF cameras, phase shift sampling is used to measure amplitude, phase and the offset (intensity) of the received signal. Each of these measurements has an associated statistical distribution that affects the SNR of the TOF signal, limiting the reliability of 3D range data. It is crucial to understand the statistical distributions of these three parameters for accurate distance measurement analysis especially in low SNR scenarios. In this paper, we provide explicit noise models for the three parameters of amplitude, phase and intensity. We use this analysis to provide an improved estimation of error in range measurement.