Instant 3D Object Tracking with Application in Augmented Reality
Abstract
Tracking object poses in 3D is an important technology in augmented reality applications.
We propose an instant motion tracking system that tracks the object's pose (3D bounding box) in real-time on mobile devices. Our system does not require any prior sensory calibration or initialization sequence to perform.
Objects are detected and their initial 3D pose is estimated using a deep neural network.
Then the estimated pose is tracked using a robust planar tracker.
Our tracker is capable of performing relative-scale 6-DoF tracking in real-time on mobile devices.
By combining CPU and GPU usage efficiently, we get 25-FPS+ performance on mobile devices.
We propose an instant motion tracking system that tracks the object's pose (3D bounding box) in real-time on mobile devices. Our system does not require any prior sensory calibration or initialization sequence to perform.
Objects are detected and their initial 3D pose is estimated using a deep neural network.
Then the estimated pose is tracked using a robust planar tracker.
Our tracker is capable of performing relative-scale 6-DoF tracking in real-time on mobile devices.
By combining CPU and GPU usage efficiently, we get 25-FPS+ performance on mobile devices.
Research Areas
