Real-Time Object Pose Tracking System With Low Computational Cost for Mobile Devices
Real-time object pose estimation and tracking is challenging but essential for some emerging applications, such as augmented reality. In general, state-of-the-art methods address this problem using deep neural networks, which indeed yield satisfactory results. Nevertheless, the high computational co...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Journal of Indoor and Seamless Positioning and Navigation |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10352604/ |
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