C. Mourning, D. Chelberg, Ronaldo Vigo, Derek E. Zeigler
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引用次数: 0
摘要
基于图像的冒名顶替者在使用基于图像的冒名顶替者时,会出现一种常见的错误,即被真实几何遮挡的场景部分是可见的。这些伪影是由相机运动产生的视差误差的结果,其中在冒名顶替生成时不可见的网格区域已经变得可见。本文分析了一种计算成本低廉的在线技术[mouring et al. 2014],通过在新的几何形状上拉伸现有的冒名顶替者[Maciel and Shirley 1995]纹理信息来弥合冒名顶替者之间的差距,从而解决这些脱节问题。[莫宁等人,2014]与传统技术相比,只提出了显示图像质量改善的自动指标;为了证实[莫宁et al. 2014]中的发现,进行了人体试验,以确定人类受试者是否发现了类似的图像质量提高。结果显示,与传统的冒名顶替者相比,其图像质量在统计学上有显著改善。
Image based imposters suffer from common errors called disocclusion artifacts where portions of the scene that should be occluded by real geometry are visible when using image based imposters. These artifacts are the result of parallax error created by camera motion where regions of a mesh that were not visible at the time of imposter generation have become visible. This document presents an analysis of a computationally inexpensive on-line technique [Mourning et al. 2014] to resolve these disocclusions by stretching existing imposter [Maciel and Shirley 1995] texture information over new geometry bridging the gap between imposters. [Mourning et al. 2014] only presented automatic metrics showing improved image quality compared to traditional techniques; in order to corroborate the findings in [Mourning et al. 2014], human trials were performed to determine if human subjects found a similar increase in image quality. Results show a statistically significant improvement in image quality over traditional imposters.