Paper Info
Title
FaceCollage: A Rapidly Deployable System for Real-time Head Reconstruction for On-The-Go 3D Telepresence.
Abstract
This paper presents FaceCollage, a robust and real-time system for head reconstruction that can be used to create easy-to-deploy telepresence systems, using a pair of consumer-grade RGBD cameras that provide a wide range of views of the reconstructed user. A key feature is that the system is very simple to rapidly deploy, with autonomous calibration and requiring minimal intervention from the user, other than casually placing the cameras. This system is realized through three technical contributions: (1) a fully automatic calibration method, which analyzes and correlates the left and right RGBD faces just by the face features; (2) an implementation that exploits the parallel computation capability of GPU throughout most of the system pipeline, in order to attain real-time performance; and (3) a complete integrated system on which we conducted various experiments to demonstrate its capability, robustness, and performance, including testing the system on twelve participants with visually-pleasing results.
Year
DOI
Venue
2017
10.1145/3123266.3123281
MM '17: ACM Multimedia Conference Mountain View California USA October, 2017
Keywords
Field
DocType
3D telepresence, RGBD sensors, face capture
Computer vision,Computer graphics (images),Computer science,Exploit,Robustness (computer science),Artificial intelligence,Calibration
Conference
ISBN
Citations 
PageRank 
978-1-4503-4906-2
2
0.37
References 
Authors
24
5
Name
Order
Citations
PageRank
Fuwen Tan182.47
Chi-Wing Fu2124493.30
Teng Deng381.17
jianfei cai41804147.18
Tat-jen Cham5100688.85