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Open AccessJournal ArticleDOI

The farthest point strategy for progressive image sampling

TLDR
A new method of farthest point strategy for progressive image acquisition-an acquisition process that enables an approximation of the whole image at each sampling stage-is presented, retaining its uniformity with the increased density, providing efficient means for sparse image sampling and display.
Abstract
A new method of farthest point strategy (FPS) for progressive image acquisition-an acquisition process that enables an approximation of the whole image at each sampling stage-is presented. Its main advantage is in retaining its uniformity with the increased density, providing efficient means for sparse image sampling and display. In contrast to previously presented stochastic approaches, the FPS guarantees the uniformity in a deterministic min-max sense. Within this uniformity criterion, the sampling points are irregularly spaced, exhibiting anti-aliasing properties comparable to those characteristic of the best available method (Poisson disk). A straightforward modification of the FPS yields an image-dependent adaptive sampling scheme. An efficient O(N log N) algorithm for both versions is introduced, and several applications of the FPS are discussed.

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Proceedings ArticleDOI

A Point Set Generation Network for 3D Object Reconstruction from a Single Image

TL;DR: This paper addresses the problem of 3D reconstruction from a single image, generating a straight-forward form of output unorthordox, and designs architecture, loss function and learning paradigm that are novel and effective, capable of predicting multiple plausible 3D point clouds from an input image.
Book

Computational geometry

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A Point Set Generation Network for 3D Object Reconstruction from a Single Image

TL;DR: In this article, the authors address the problem of 3D reconstruction from a single image, generating a straight-forward form of output -point cloud coordinates. But the groundtruth shape for an input image may be ambiguous, and they design architecture, loss function and learning paradigm that are novel and effective.
Journal ArticleDOI

Generalized multidimensional scaling: A framework for isometry-invariant partial surface matching

TL;DR: The generalized multidimensional scaling algorithm is introduced, a computationally efficient continuous optimization algorithm for finding the least distortion embedding of one surface into another that allows for both full and partial surface matching.
Journal ArticleDOI

Scattered data interpolation methods for electronic imaging systems: a survey

TL;DR: The main methods reviewed include linear triangular (or tetrahedral) interpolation, cubic triangular (Clough-Tocher) interpo- lation, triangle based blending interpolations, inverse distance weighted methods, radial basis function methods, and natural neigh- bor interpolation methods.
References
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Random variables and stochastic processes

TL;DR: An electromagnetic pulse counter having successively operable, contact-operating armatures that are movable to a rest position, an intermediate position and an active position between the main pole and the secondary pole of a magnetic circuit.
Journal ArticleDOI

Voronoi diagrams—a survey of a fundamental geometric data structure

TL;DR: The Voronoi diagram as discussed by the authors divides the plane according to the nearest-neighbor points in the plane, and then divides the vertices of the plane into vertices, where vertices correspond to vertices in a plane.
Book

Computational geometry

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