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.
@article{arxiv.2006.13194,
title = {Instant 3D Object Tracking with Applications in Augmented Reality},
author = {Adel Ahmadyan and Tingbo Hou and Jianing Wei and Liangkai Zhang and Artsiom Ablavatski and Matthias Grundmann},
journal= {arXiv preprint arXiv:2006.13194},
year = {2020}
}
Comments
4 pages, five figures, CVPR Fourth Workshop on Computer Vision for AR/VR