LiDAR motion capture uses Bézier curves for improved accuracy

Researchers have developed a new framework called BMLiCap for more accurate 3D human motion capture using LiDAR data. This method employs Bézier curves to represent motion, which helps in creating a more coherent and learnable representation by reducing control points while preserving trajectory. The framework includes a Time-scale Motion Transformer and a Multi-level Motion Aggregator to reconstruct detailed poses from multi-scale motion curves, effectively handling occlusions and noise. AI

影响 Introduces a novel approach to motion capture that could improve applications in robotics and autonomous driving by handling occlusions and noise more effectively.

排序理由 The cluster contains an academic paper detailing a new method for LiDAR-based human motion capture. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

• BMLiCap
• FreeMotion
• LiDAR
• LiDARHuman26M
• Multi-level Motion Aggregator
• NoiseMotion
• SLOPER4D
• Time-scale Motion Transformer
• Bézier curves

• 论文
• 其他

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