Phong Surface: Efficient 3D Model Fitting using Lifted Optimization

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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.

See more at https://www.microsoft.com/en-us/research/video/phong-surface-efficient-3d-model-fitting-using-lifted-optimization/




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Tags:
Phong Surface
mixed reality
real time 3D
HoloLens 2
hand tracking
triangulated mesh model
Jingjing Shen
Microsoft Research
computer vision
Microsoft Research Cambridge
ECCV 2020
lifted optimization