计算机科学 ›› 2021, Vol. 48 ›› Issue (11): 226-233.doi: 10.11896/jsjkx.201200095
穆逢君1, 邱静1, 陈路锋2, 黄瑞2, 周林3, 于功敬3
MU Feng-jun1, QIU Jing1, CHEN Lu-feng2, HUANG Rui2, ZHOU Lin3, YU Gong-jing3
摘要: 现有的物体姿态估计方法无法提供具有帧间稳定性的估计姿态,导致将其结果直接用于增强现实等可视化场景时会引起画面抖动,不适用于人机协同等应用场景。文中提出了一种包含多种方式的物体姿态估计优化方法,通过对原始姿态估计方法的损失函数的改进,并使用因果滤波的方法优化姿态估计结果,以获得具有稳定性的估计姿态。此外,为完善对姿态估计方法稳定程度的评价体系,文中提出了直接偏差距离DBD、方向反转率DRR与平均位移角ADA 3种评价指标,可以从多个角度对物体姿态估计方法的帧间稳定性进行评价。最后,使用YCB-STB数据集作为测试样本,并将所提方法与未经优化的原始方法进行对比测试。结果表明,所提方法可在不引入额外资源开销的情况下提高现有物体姿态估计方法的帧间稳定性,且对原始方法的准确率影响较小,满足了人机协同场景对物体姿态估计结果的需求。
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