SCI: SGER: Application Directed Surface Parameterization

该SGER建立在以前NSF资助的工作基础上，为图形处理器（GPU）开发新算法，如光线跟踪，矩阵乘法，辐射度和辐射热传递，次表面散射，辐射传递，聚类，场景图形处理和动态自适应表面采样。在这些领域的进展，使PI提出重点探索目标导向的参数化和研究优化方法映射网格表面的平面域的基础上新的指标。具体而言，工作建议扩展目前的支持动态多分辨率网格地图集，包括能力，以处理移动表面域在一个交互式的模型上下文中，没有损失的细节。这项工作与前面提到的开发应用程序驱动的指标的工作相平衡。

This SGER builds off previous NSF-funded work in developing new algorithms for graphics processors (GPUs) in areas such as ray tracing, matrix multiplication, radiosity and radiative heat transfer, subsurface scattering, radiance transfer, clustering, scene graph processing, and dynamic adaptive surface sampling. Advances in these areas allow the PI to propose focused exploration in goal-directed parameterization and investigate optimization methods for mapping meshed surfaces to a planar domain based on new metrics. Specifically, work is proposed to extend the current support for dynamic multiresolution meshed atlas to include capability to deal with moving surface domains in an interactive model context with no loss of detail. That work is balanced with the aforementioned work in developing application-driven metrics.