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.
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Belhedi, A., Bartoli, A., Bourgeois, S., Hamrouni, K., Sayd, P., Gay-Bellile, V. (2012). Noise Modelling and Uncertainty Propagation for TOF Sensors. In: Fusiello, A., Murino, V., Cucchiara, R. (eds) Computer Vision – ECCV 2012. Workshops and Demonstrations. ECCV 2012. Lecture Notes in Computer Science, vol 7585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33885-4_48
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DOI: https://doi.org/10.1007/978-3-642-33885-4_48
Publisher Name: Springer, Berlin, Heidelberg
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