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    Hashed, binned A-buffer for real-time outlier removal and rendering of noisy point clouds
    Typical point-based rendering algorithms cannot directly handle large outliers or high amounts of noise without either a costly pre-processing of the point cloud or using multiple render passes. In this paper, we propose an A-buffer-based approach that directly renders unprocessed point clouds and filters out outliers in real time, without introducing additional render passes. The core concept of our approach uses bins along each pixel ray in which intermediate information is accumulated. To improve storage efficiency, we extend the binned A-buffer approach using per-ray bin hashing. Our method significantly improves visual quality when rendering noisy point clouds with varying noise levels and large outliers, while only requiring little performance and memory overhead compared to traditional point rendering methods.
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    PublicationAccess status: Open Access ,
    Pulse based Time-of-Flight range sensing
    Pulse-based Time-of-Flight (PB-ToF) cameras are an attractive alternative range imaging approach, compared to the widely commercialized Amplitude Modulated Continuous-Wave Time-of-Flight (AMCW-ToF) approach. This paper presents an in-depth evaluation of a PB-ToF camera prototype based on the Hamamatsu area sensor S11963-01CR. We evaluate different ToF-related effects, i.e., temperature drift, systematic error, depth inhomogeneity, multi-path effects, and motion artefacts. Furthermore, we evaluate the systematic error of the system in more detail, and introduce novel concepts to improve the quality of range measurements by modifying the mode of operation of the PB-ToF camera. Finally, we describe the means of measuring the gate response of the PB-ToF sensor and using this information for PB-ToF sensor simulation
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