Pose estimates from online videos show that side-by-side walkers synchronize movement under naturalistic conditions
Pose estimates from online videos show that side-by-side walkers synchronize movement under naturalistic conditions
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DOI：
10.1371/journal.pone.0217861
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发表时间：
2019-06-06
期刊：
影响因子：
3.7
通讯作者：
Kording, Konrad
中科院分区：
文献类型：
--
作者：
Chambers, Claire;Kong, Gaiqing;Kording, Konrad
基于无标记视频的姿态估计有望使我们能够在现有的视频数据库上进行运动科学。我们重新讨论了人们如何使用真实的世界数据同步行走的老问题。因此，我们将姿势估计应用于从YouTube视频中提取的348个视频片段，这些视频片段是人们在城市中行走的视频。在之前的研究中，我们发现了一种趋势，即成对的人彼此同相或反相行走。大型视频数据库，沿着的姿态估计算法，承诺许多运动问题的答案，而无需实验获取新的数据。
Marker-less video-based pose estimation promises to allow us to do movement science on existing video databases. We revisited the old question of how people synchronize their walking using real world data. We thus applied pose estimation to 348 video segments extracted from YouTube videos of people walking in cities. As in previous, more constrained, research, we find a tendency for pairs of people to walk in phase or in anti-phase with each other. Large video databases, along with pose-estimation algorithms, promise answers to many movement questions without experimentally acquiring new data.