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arXiv Computer Vision By Lewis de Zoete Grundy, Chris McCarthy, Christopher Fluke

Pose-Anchored Optical Flow for Low-Latency Human Action Anticipation in Human-Robot Teaming

Read the original on arXiv Computer Vision →

Pose-Anchored Optical Flow for Low-Latency Human Action Anticipation in Human-Robot Teaming proposes PoseOFF, a representation that captures local motion around human joints by conditioning optical flow extraction on pose. This structured motion representation aligns with human kinematics and improves early action recognition accuracy across multiple datasets and backbones. PoseOFF achieves comparable or better performance while observing less of the action sequence, making it suitable for real‑time, resource‑constrained robotic systems.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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