View-dependent information theory quality measures for pixel sampling and scene discretization in flatland

Jaume Rigau, M. Feixas, M. Sbert, P. Bekaert
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引用次数: 3

Abstract

In this paper, we present view-dependent information theory quality measures for pixel sampling and scene discretization in flatland. The measures are based on a definition for the mutual information of a line, and have a purely geometrical basis. Several algorithms exploiting them are presented and compare well with an existing one based on depth differences.
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平面上像素采样和场景离散化的视点依赖信息理论质量度量
在本文中,我们提出了基于视点依赖的信息理论的平面像素采样和场景离散的质量度量。这些措施是基于对一条线的相互信息的定义,并具有纯粹的几何基础。提出了几种利用深度差的算法,并与现有的基于深度差的算法进行了比较。
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Some new challenging research topics in human animation High precision non-binary voxelization of geometric objects View-dependent information theory quality measures for pixel sampling and scene discretization in flatland A colour reindexing algorithm for lossless compression of digital images Parallel triangular mesh decimation without sorting
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