@inproceedings{shen2020the,
author = {Shen, Jingjing and Cashman, Tom and Ye, Qi and Hutton, Tim and Sharp, Toby and Bogo, Federica and Fitzgibbon, Andrew and Shotton, Jamie},
title = {The Phong Surface: Efficient 3D Model Fitting Using Lifted Optimization},
booktitle = {2020 European Conference on Computer Vision},
year = {2020},
month = {August},
abstract = {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.},
publisher = {Springer, Cham},
url = {http://approjects.co.za/?big=en-us/research/publication/the-phong-surface-efficient-3d-model-fitting-using-lifted-optimization/},
pages = {687-703},
}