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3D Reconstruction from Depth and Stereo Images for Augmented Reality Application - Antoine Mischler

Lupe [1]

In this thesis, we introduce a framework for augmented reality applications that require depth information in real-time. We combine time-of-flight (TOF) range imaging based on the photonic mixing device principle with stereo vision. The data is merged at interactive frame rates, providing depth maps that are more reliable and accurate than the ones from either of the sensors. The confidence of the TOF depth data is estimated. The resulting confidence map is used in two ways. First, with the TOF depth data we initialize and constrain the disparity range of the stereo algorithm. Second, we segment the images according to the color information and depth confidence information. This segmentation produces depth-continuous data areas.  It allows to adapt the correlation window to the depth data. The first part helps avoiding unnecessary computations and disambiguating disparities and the second part increases the stability near depth discontinuities. This algorithm produces accurate and reliable depth maps and we use them in augmented reality setups. We show that this range data can be used to handle accurate visual occlusions and physical interactions between virtual objects and the real world.

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