TP-AE: Temporally Primed 6D Object Pose Tracking with Auto-Encoders

Zheng，Linfang1,2; Leonardis，Ales2; Tse，Tze Ho Elden2; Horanyi，Nora2; Chen，Hua1; Zhang，Wei1; Chang，Hyung Jin2

10.1109/ICRA46639.2022.9811890

2022

1050-4729

978-1-7281-9682-4

Proceedings - IEEE International Conference on Robotics and Automation

10616-10623

23-27 May 2022

Philadelphia, PA, USA

Fast and accurate tracking of an object's motion is one of the key functionalities of a robotic system for achieving reliable interaction with the environment. This paper focuses on the instance-level six-dimensional (6D) pose tracking problem with a symmetric and textureless object under occlusion. We propose a Temporally Primed 6D pose tracking framework with Auto-Encoders (TP-AE) to tackle the pose tracking problem. The framework consists of a prediction step and a temporally primed pose estimation step. The prediction step aims to quickly and efficiently generate a guess on the object's real-time pose based on historical information about the target object's motion. Once the prior prediction is obtained, the temporally primed pose estimation step embeds the prior pose into the RGB-D input, and leverages auto-encoders to reconstruct the target object with higher quality under occlusion, thus improving the framework's performance. Extensive experiments show that the proposed 6D pose tracking method can accurately estimate the 6D pose of a symmetric and textureless object under occlusion, and significantly outperforms the state-of-the-art on T-LESS dataset while running in real-time at 26 FPS.

Target tracking Automation Pose estimation Real-time systems Reliability Robots

First ; Corresponding

English

EI

20223312572577

Gesture recognition ; Robotics ; Signal encoding ; Textures

Information Theory and Signal Processing:716.1 ; Robotics:731.5

2-s2.0-85136335236

Scopus

1.Southern University of Science and Technology (SUSTech),Department of Mechanical and Energy Engineering,China
2.School of Computer Science,University of Birmingham,United Kingdom

Zheng，Linfang,Leonardis，Ales,Tse，Tze Ho Elden,et al. TP-AE: Temporally Primed 6D Object Pose Tracking with Auto-Encoders[C],2022:10616-10623.