“…∇H t represents the discrete gradient of H t , |.| denotes the L1-norm and µ is the regularization parameter. BTV regularization/denoising has been a topic of interest for researchers but most of the research has been restricted to organized color and depth images [28,33,36,39,42], where the neighborhoods are well defined and the gradient, based on intensity or depth values, is easy to compute e.g., via shift operators [34,51]. In the current problem,Ĥ f t is a set of unorganized 3D points without any connectivity or neighborhood information, therefore the extension of BTV regularization to 3D point clouds is not a straightforward problem.…”