An Improved Approach to 6D Object Pose Tracking in Fast Motion Scenarios-Reference-Cited by-同舟云学术

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An Improved Approach to 6D Object Pose Tracking in Fast Motion Scenarios

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 Sixth IEEE International Conference on Robotic Computing (IRC)
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Author:

Wu Yanming¹,Vandewalle Patrick²,Slaets Peter³,Demeester Eric¹

Affiliation:

1. KU Leuven, Research unit ACRO,Department of Mechanical Engineering,Diepenbeek,Belgium,3590

2. KU Leuven, Research unit PSI,Department of Electrical Engineering,Sint-Katelijne-Waver,Belgium,2860

3. KU Leuven, Research unit IMP,Department of Mechanical Engineering,Leuven,Belgium,3000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10023545/10022323/10023869.pdf?arnumber=10023869

Reference33 articles.

1. A New Quaternion-Based Kalman Filter for Real-Time Attitude Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm

2. Quaternions and Rotation Sequences

3. Estimation with applications to tracking and navigation: theory algorithms and software;bar-shalom;John Wiley & Sons,2004

4. Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size;iandola;arXiv preprint arXiv 1602 07360,2016

5. DART: Dense Articulated Real-Time Tracking

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DeepKalPose: An enhanced deep‐learning Kalman filter for temporally consistent monocular vehicle pose estimation;Electronics Letters;2024-04

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