This paper introduces the Half Pound Filter (HPF) as a modification of the 1 Euro Filter (1EF) and algorithms for automatic data-driven tuning and for filter triggering based on motion derivative boundary checks. An application of the filter is presented in the context of human animation replay for real-time simulations, where switches in animation clips cause discontinuities that must be hidden by filtering the bone trajectory without introducing noticeable artifacts. The quality of the filtering will be compared with other common animation filtering techniques using an example case drawn fromthe LaFAN1 dataset, showing that the resulting animation is replayed with higher fidelity by evaluating the Mean Squared Error (MSE) and Normalized Power Spectrum Similarity (NPSS) for each setup. Performances will be evaluated using both a standard predetermined triggerpoint and blending distance and the automatic blending trigger and recovery system.

翻译：本文提出半磅滤波器（HPF），作为对1欧元滤波器（1EF）的改进，并介绍了基于数据驱动的自动调参算法以及基于运动导数边界检测的滤波器触发算法。该滤波器应用于实时仿真中的人类动画回放场景，通过处理骨骼轨迹来消除动画片段切换时产生的不连续性，同时避免引入明显伪影。研究采用LaFAN1数据集中的案例，通过计算均方误差（MSE）和归一化功率谱相似度（NPSS）指标，将本滤波效果与其他常见动画滤波技术进行对比，结果表明该方法能以更高保真度回放动画。性能评估将同时采用预设触发点与混合距离的传统方案，以及自动混合触发恢复系统进行验证。