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. © 2012 Springer-Verlag.
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CITATION STYLE
Belhedi, A., Bartoli, A., Bourgeois, S., Hamrouni, K., Sayd, P., & Gay-Bellile, V. (2012). Noise modelling and uncertainty propagation for TOF sensors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7585 LNCS, pp. 476–485). Springer Verlag. https://doi.org/10.1007/978-3-642-33885-4_48
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