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In this paper we present an approach to indoor localization and 3D scene reconstruction using the Microsoft Kinect sensor. The proposed system can simultaneously estimates the position and orientation of a hand-held Kinect and generates a dense 3D model of the indoor environment. Furthermore, the robustness and processing time for four different feature descriptors (SURF, ORB, Shi-Tomasi and FAST) are evaluated. The experiment results demonstrate that our system can robustly deal with complicated data in common indoor scenarios while running in semi-real-time.
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Zou et al. (2012) studied this question.
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