Feature-preserving Denoising of Time-varying Range Data

Introduction We present a technique for accurate denoising of time-varying range data. It is inspired by the idea of similarity-based non-local image filtering [Buades et al. 2005] and spatio-temporal bilateral filtering for video processing [Bennett and McMillan 2005]. We build upon both ideas and are to our knowledge the first method which extends them to time-varying geometric data. Our proposed algorithm is easy to implement, preserves fine shape features and produces an accurate and homogeneous smoothing result in the spatial and along the time domains. 2 Method Overview Our scanning device provides data points p i arranged on a regular grid structure for all frames of the sequence. In this way, the neighborhood information for all points is known, but they are not required to be equispaced. Hence, our problem is different from image denoising, where points are usually aligned on a regular and equispaced grid. Since this data representation is also standard for range data acqu