论文标题
Instant 3D对象跟踪具有增强现实中的应用程序
Instant 3D Object Tracking with Applications in Augmented Reality
论文作者
论文摘要
在3D中跟踪对象姿势是增强现实应用程序的关键构建块。我们提出了一个即时运动跟踪系统，该系统在移动设备上实时跟踪对象的姿势（由其3D边界框表示）。我们的系统不需要任何事先的感觉校准或初始化才能发挥作用。我们采用深层神经网络来检测物体并估算其最初的3D姿势。然后使用健壮的平面跟踪器跟踪估计的姿势。我们的跟踪器能够在移动设备上实时执行相对规模的9-DOF跟踪。通过有效地组合CPU和GPU的使用，我们在移动设备上实现了26-FPS+性能。
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.
