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首页> 外文期刊>IEEE transactions on multimedia >Factorization Algorithms for Temporal Psychovisual Modulation Display
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Factorization Algorithms for Temporal Psychovisual Modulation Display

机译:时间心理视觉调制显示的因式分解算法

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摘要

Temporal psychovisual modulation (TPVM) is a new information display technology which aims to generate multiple visual percepts for different viewers on a single display simultaneously. In a TPVM system, the viewers wearing different active liquid crystal (LC) glasses with varying transparency levels can see different images (called personal views). The viewers without LC glasses can also see a semantically meaningful image (called shared view). The display frames and weights for the LC glasses in the TPVM system can be computed through nonnegative matrix factorization (NMF) with three additional constrains: 1) the values of images and modulation weights should have upper bound (i.e., limited luminance of the display and transparency level of the LC); 2) the shared view without using viewing devices should be considered (i.e., the sum of all basis images should be a meaningful image); and 3) the sparsity of modulation weights should be considered due to the material property of LC. In this paper, we proposed to solve the constrained NMF problem by a modified version of hierarchical alternating least squares (HALS) algorithms. Through experiments, we analyze the choice of parameters in the setup of TPVM system. This work serves as a guideline for practical implementation of TPVM display system.
机译:时间心理视觉调制(TPVM)是一种新的信息显示技术,旨在同时在单个显示器上为不同的观看者生成多种视觉感知。在TPVM系统中,观看者佩戴具有不同透明度的不同有源液晶(LC)眼镜时,他们可以看到不同的图像(称为个人视图)。没有LC眼镜的观看者还可以看到语义上有意义的图像(称为共享视图)。 TPVM系统中LC眼镜的显示帧和权重可以通过非负矩阵分解(NMF)并具有三个附加约束来计算:1)图像和调制权重的值应具有上限(即,显示器的亮度有限,并且信用证的透明度); 2)应该考虑不使用查看设备的共享视图(即所有基本图像的总和应该是有意义的图像); 3)由于LC的材料特性,应考虑调制权重的稀疏性。在本文中,我们提出了通过改进的分层交替最小二乘(HALS)算法来解决约束NMF问题。通过实验,我们分析了TPVM系统设置中的参数选择。这项工作为TPVM显示系统的实际实施提供了指导。

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