Instant 3D Object Tracking with Applications in Augmented Reality
This enables instant, efficient AR applications on mobile devices, but it is incremental as it combines existing detection and tracking methods.
The paper tackles the problem of real-time 3D object tracking for augmented reality on mobile devices, achieving over 26 FPS without prior calibration.
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.