English

Bringing Telepresence to Every Desk

Computer Vision and Pattern Recognition 2023-04-04 v1 Graphics

Abstract

In this paper, we work to bring telepresence to every desktop. Unlike commercial systems, personal 3D video conferencing systems must render high-quality videos while remaining financially and computationally viable for the average consumer. To this end, we introduce a capturing and rendering system that only requires 4 consumer-grade RGBD cameras and synthesizes high-quality free-viewpoint videos of users as well as their environments. Experimental results show that our system renders high-quality free-viewpoint videos without using object templates or heavy pre-processing. While not real-time, our system is fast and does not require per-video optimizations. Moreover, our system is robust to complex hand gestures and clothing, and it can generalize to new users. This work provides a strong basis for further optimization, and it will help bring telepresence to every desk in the near future. The code and dataset will be made available on our website https://mcmvmc.github.io/PersonalTelepresence/.

Keywords

Cite

@article{arxiv.2304.01197,
  title  = {Bringing Telepresence to Every Desk},
  author = {Shengze Wang and Ziheng Wang and Ryan Schmelzle and Liujie Zheng and YoungJoong Kwon and Soumyadip Sengupta and Henry Fuchs},
  journal= {arXiv preprint arXiv:2304.01197},
  year   = {2023}
}
R2 v1 2026-06-28T09:47:22.982Z