Communications in Information and Systems

Volume 23 (2023)

Number 2

TSDFFilter: content-aware communication planning for remote 3D reconstruction

Pages: 213 – 239



Xu-Qiang Hu (Department of Computer Science and Technology, Tsinghua University, Beijing, China)

Yu-Ping Wang (School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China)

Zi-Xin Zou (Department of Computer Science and Technology, Tsinghua University, Beijing, China)

Dinesh Manocha (Department of Computer Science, University of Maryland, College Park, Md., U.S.A.)


We present a novel solution, TSDFFilter, for remote 3D reconstruction to relieve the high bandwidth requirement problem. Our approach is designed for scenarios where agents are used to collect data using an RGB‑D camera and then transmit the information over the regular network to a high-performance server, where a global, dense, and volumetric model of a real-world scene is reconstructed. Our approach uses a content-aware communication planning framework in which agents can prune the gathered RGBD information according to the transmission policy generated by the server. To generate the transmission policy, we introduce a confidence value to estimate how much each RGB‑D pixel contributes to the reconstruction quality, and present an algorithm to find the confidence value. As a result, agents can transmit less RGB‑D information without blindly compromising the reconstruction quality as the key-frame method and down-sampling method do. We implement our TSDFFilter framework to achieve real-time agent-assisted 3D reconstruction. Extensive evaluations show that comparing with the key-frame and down-sampling methods, our TSDFFilter framework can reduce the bandwidth requirement by up to 36% with similar reconstruction Chamfer distance, and reduce the reconstruction Chamfer distance by up to 78% with similar bandwidth requirement.


communication planning, remote 3D reconstruction, TSDF, transmission policy

Received 20 January 2023

Published 7 August 2023