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Noise Modelling and Uncertainty Propagation for TOF SensorsAmira Belhedi1, 2, 3, Adrien Bartoli2, Steve Bourgeois1, Kamel Hamrouni3, Patrick Sayd1, and Vincent Gay-Bellile1 1CEA, LIST, LVIC, France
2Clermont Université, Université d’Auvergne, ISIT, France
3Université de Tunis El Manar, ENIT, SITI, Tunisia
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. LNCS 7585, p. 476 ff. lncs@springer.com
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