English(EN) HAP: A Hand-Driven Active Perception Framework for Egocentric Head Motion Prediction

新框架预测物体操作过程中的头部运动

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-17 04:00

研究人员开发了HAP，一个手驱动主动感知框架，旨在预测物体操作过程中人类的头部运动。该框架考虑了手部运动、推断的目标上下文以及物体间的动态遮挡，以预测头部运动。HAP在一个名为Bottle的新数据集上进行了测试，该数据集捕获了物体操作的自我中心RGB-D数据，并证明其预测精度优于现有方法。 AI

影响这项研究可以通过更准确地预测操作任务中人类的注意力转移和运动，从而改善人机交互和具身AI。

排序理由该集群描述了一篇详细介绍新颖的自我中心运动预测框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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本文如何被排名

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Newsworthiness bucket: Tool; 该集群描述了一篇详细介绍新颖的自我中心运动预测框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.CV TIER_1 English(EN) · Yunji Feng, Junyi Ma, Guanzhong Sun, Chenyang Xu, Hesheng Wang · 2026-09-17 04:00

HAP：一种用于以自我为中心头部运动预测的手动主动感知框架

arXiv:2609.18548v1 Announce Type: new Abstract: Egocentric motion forecasting has primarily focused on hands and manipulated objects, leaving future human head motion comparatively underexplored. During manipulation, the head both redirects perception toward the target to acquire…