Many researches on efficient depth maps coding issues have been carried out giving particular attention to sharp edge
preservation. Platelet-based coding method is an edge-aware coding scheme that uses a segmentation procedure based
on recursive quadtree decomposition. Then, the depth map is modeled using piecewise linear platelet and wedgelet
functions. However, the estimation of these functions is a computationally expensive task making the platelet-based
techniques not adapted to online applications. In this paper, we propose to exploit edge detection in order to reduce the
encoding delay of the platelet/wedgelet estimation process. The proposed approach shows significant gain in terms of
encoding delay, while providing competitive R-D performances w.r.t. the original platelet-based codec. The subjective
evaluation shows significant less degradation along sharp edges.
This paper deals with three-dimensional (3D) surface reconstruction from unorganized set of points. Several methods have been developed in the literature. Most of them are based on the 3D Delaunay triangulation. We propose a new method that transforms a set of points into contours in 3D space. This transformation seems to be interesting because the problem of surface reconstruction from contours was widely studies. The triangulation process is composed of the following steps: slicing, 3D curve extraction and tiling. The tiling step is an extension of a well known algorithm used generally for connecting parallel adjacent planar slices. In order to evaluate the performance of our method, we compare it with two well known 3D Delaunay triangulation based methods called α-shape and 3D Crust. We focus on three different comparison criteria: the complexity, the visualization quality and two additional geometrical criteria: the triangulation quality and the rugosity degree.
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