Cloud Dictionary: Sparse Coding and Modeling for Point Clouds Article Swipe

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Point cloud Computer science Grid Artificial intelligence Computer vision Lidar Coding (social sciences) Range (aeronautics) Point (geometry) Cloud computing Cartesian coordinate system Neural coding Regular grid Noise reduction Remote sensing Geography Mathematics Engineering Statistics Aerospace engineering Geodesy Geometry Operating system

Or Litany , Tal Remez , Alexander M. Bronstein ·

YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1612.04956 · OA: W2582151442

With the development of range sensors such as LIDAR and time-of-flight cameras, 3D point cloud scans have become ubiquitous in computer vision applications, the most prominent ones being gesture recognition and autonomous driving. Parsimony-based algorithms have shown great success on images and videos where data points are sampled on a regular Cartesian grid. We propose an adaptation of these techniques to irregularly sampled signals by using continuous dictionaries. We present an example application in the form of point cloud denoising.