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Extended abstract of Ph. D thesis noise modeling and depth calibration for time-of-flight cameras

Abstract : 3D cameras open new perspectives in different application fields such as 3D reconstruction, Augmented Reality and video-surveillance since they provide depth information at high frame-rates. However, they have limitations that affect the accuracy of their measures. In particular for TOF (Time-Of-Flight) cameras, two types of error can be distinguished: stochastic noise of the camera and the depth distortion. This is illustrated in the figure 1 where a depth image of a cube is presented. The pixel ($x, y$) is the depth measure of the 3D point $Q$. This depth measure ($d_{TOF}$) is compared to the real depth $d_{GT}$. $d_{TOF}$ corresponds to a distorted measure of $d_{GT}$ in addition to the stochastic noise.
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https://hal-cea.archives-ouvertes.fr/cea-01753220
Contributor : Léna Le Roy <>
Submitted on : Thursday, March 29, 2018 - 3:12:53 PM
Last modification on : Monday, February 10, 2020 - 6:13:48 PM

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A. Belhedi. Extended abstract of Ph. D thesis noise modeling and depth calibration for time-of-flight cameras. Electronic Letters on Computer Vision and Image Analysis, Computer Vision Center Press, 2014, 13, pp.51-53. ⟨cea-01753220⟩

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