Fast Vision-based 3D Indoor Localization and Tracking for Commodity Hardware

  • Chang H.
  • Lakshman T.
  • Yun D.

In real-time augmented reality applications, it is important to find and track the 3D position and orientation of a moving camera with high accuracy. However, it is challenging to compute a camera's 3D trajectories at high frequency on commodity hardware because the computation involves heavy-weight 2D-3D matching process. In this paper, we propose a fast vision-based 3D indoor localization and tracking system which is suitable for commodity hardware. We reduce per-frame 3D tracking computation overhead by a factor of seven by splitting a camera viewpoint into multiple smaller regions, and processing only one region at a time for each frame. When the absolute 3D location or sufficient keypoints are needed prior to 3D tracking, we rely on the cloud for fast 3D positioning. From prototype experiments, we demonstrate that our system can conduct sub-meter accuracy 3D tracking at 20-30 fps in a large-scale indoor hallway environment.

Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...