KTH Royal Institute of Technology, Stockholm, Sweden.
Swedish University of Agricultural Sciences, Uppsala, Sweden.
Sci Data. 2024 May 15;11(1):497. doi: 10.1038/s41597-024-03312-1.
Studies of quadruped animal motion help us to identify diseases, understand behavior and unravel the mechanics behind gaits in animals. The horse is likely the best-studied animal in this aspect, but data capture is challenging and time-consuming. Computer vision techniques improve animal motion extraction, but the development relies on reference datasets, which are scarce, not open-access and often provide data from only a few anatomical landmarks. Addressing this data gap, we introduce PFERD, a video and 3D marker motion dataset from horses using a full-body set-up of densely placed over 100 skin-attached markers and synchronized videos from ten camera angles. Five horses of diverse conformations provide data for various motions from basic poses (eg. walking, trotting) to advanced motions (eg. rearing, kicking). We further express the 3D motions with current techniques and a 3D parameterized model, the hSMAL model, establishing a baseline for 3D horse markerless motion capture. PFERD enables advanced biomechanical studies and provides a resource of ground truth data for the methodological development of markerless motion capture.
四足动物运动的研究有助于我们识别疾病、理解行为,并揭示动物步态背后的力学原理。马在这方面可能是研究得最多的动物,但数据采集具有挑战性且耗时。计算机视觉技术可以提高动物运动的提取能力,但这种发展依赖于参考数据集,而这些数据集稀缺、非开放获取,并且通常只提供来自少数几个解剖学标记的数据。为了解决这个数据差距,我们引入了 PFERD,这是一个来自马的视频和 3D 标记运动数据集,使用了全身密集放置的超过 100 个皮肤附着标记和来自十个摄像机角度的同步视频。五匹不同形态的马提供了各种运动的数据,包括基本姿势(例如行走、小跑)到高级运动(例如站立、踢腿)。我们进一步使用当前技术和一个 3D 参数化模型,即 hSMAL 模型,表达了 3D 运动,为 3D 无标记运动捕捉建立了一个基准。PFERD 能够进行高级生物力学研究,并为无标记运动捕捉的方法学发展提供地面实况数据资源。