论文标题
phong表面：有效的3D模型使用提升优化
The Phong Surface: Efficient 3D Model Fitting using Lifted Optimization
论文作者
论文摘要
混合现实中的实时感知和互动功能需要在资源受限的硬件（例如头部安装的设备）上以低延迟来解决一系列3D跟踪问题。实际上，对于诸如HoloLens 2之类的设备，CPU和GPU可用于应用程序，需要多个跟踪子系统才能连续实时运行，同时共享一个单个数字信号处理器。为了解决HoloLens 2手跟踪的模型拟合问题，其中计算预算比iPhone 7小100倍，我们引入了一种新的表面模型：“ phong Surface”。 Phong Surface使用计算机图形的想法将相同的3D形状描述为三角形的网格模型，但具有连续的表面正态，可以使用基于提升的优化，从而比基于ICP的方法具有显着效率提高。我们表明，phong表面保留了平滑表面模型的收敛益处，而三角形网格则没有。
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.
