Noise Modelling and Uncertainty Propagation for TOF Sensors

Amira Belhedi, Adrien Bartoli, Steve Bourgeois, Kamel Hamrouni, Patrick Sayd, Vincent Gay-Bellile

Abstract: Time-of-Flight (TOF) cameras are active real time depth sensors. One issue of TOF sensors is measurement noise. In this paper, we present a method for providing the uncertainty associated to 3D TOF measurements based on noise modelling. Measurement uncertainty is the combination of pixel detection error and sensor noise. First, a detailed noise characterization is presented. Then, a continuous model which gives the noise’s standard deviation for each depth-pixel is proposed. Finally, a closed-form approximation of 3D uncertainty from 2D pixel detection error is presented. An applicative example is provided that shows the use of our 3D uncertainty modelling on real data.