Instant 3D Object Tracking with Applications in Augmented Reality

PubDate: June 2020

Teams: Matthias Grundmann，Google Research

Writers: Adel Ahmadyan‎, Tingbo Hou, Jianing Wei, Liangkai Zhang, Matthias Grundmann, Artsiom Ablavatski

PDF: Instant 3D Object Tracking with Applications in Augmented Reality

Project: Instant 3D Object Tracking with Applications in Augmented Reality

Abstract

Tracking object poses in 3D is a crucial building block for Augmented Reality applications. We propose an instant motion tracking system that tracks an object’s pose in space (represented by its 3D bounding box) in real-time on mobile devices. Our system does not require any prior sensory calibration or initialization to function. We employ a deep neural network to detect objects and estimate their initial 3D pose. Then the estimated pose is tracked using a robust planar tracker. Our tracker is capable of performing relative-scale 9-DoF tracking in real-time on mobile devices. By combining use of CPU and GPU efficiently, we achieve 26-FPS+ performance on mobile devices.