Phong曲面：使用提升优化的高效3D模型拟合
The Phong Surface: Efficient 3D Model Fitting using Lifted Optimization
摘要：
混合现实中的实时感知和交互能力需要在资源受限的硬件（如头戴式设备）上以低延迟解决一系列3D跟踪问题。事实上，对于HoloLens 2这样的设备，CPU和GPU可用于应用程序，多个跟踪子系统需要在连续实时的基础上运行，同时共享单个数字信号处理器。为了解决HoloLens 2手部跟踪的模型拟合问题，其中计算预算大约比iPhone 7小100倍，我们引入了一个新的表面模型：“Phong表面”。使用计算机图形学的思想，Phong曲面描述了与三角网格模型相同的3D形状，但具有连续的曲面法线，可以使用基于提升的优化，比基于ICP的方法提供了显着的效率提升。我们发现，Phong曲面保留了平滑曲面模型的收敛优势，而三角形网格则没有。
英文摘要：
Realtime perceptual and interaction capabilities in mixed reality require a range of 3D tracking problems to be solved at low latency on resource-constrained hardware such as head-mounted devices. Indeed, for devices such as HoloLens 2 where the CPU and GPU are left available for applications, multiple tracking subsystems are required to run on a continuous, real-time basis while sharing a single Digital Signal Processor. To solve model-fitting problems for HoloLens 2 hand tracking, where the computational budget is approximately 100 times smaller than an iPhone 7, we introduce a new surface model: the `Phong surface'. Using ideas from computer graphics, the Phong surface describes the same 3D shape as a triangulated mesh model, but with continuous surface normals which enable the use of lifting-based optimization, providing significant efficiency gains over ICP-based methods. We show that Phong surfaces retain the convergence benefits of smoother surface models, while triangle meshes do not.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
