2020/06/23 by Adel Ahmadyan, Ahmadyan, Adel, Tingbo Hou +9
Computer Science · Earth and Planetary Sciences · Engineering · #3D Surveying and Cultural Heritage #Augmented Reality Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Robotics and Sensor-Based Localization #cs.CV
paper · pdf · doi:10.48550/arxiv.2006.13194
4 pages, five figures, CVPR Fourth Workshop on Computer Vision for AR/VR
arxiv created 2020/06/23 · openalex publication_date 2020/06/23 · arxiv updated 2020/06/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.