Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analytics' research. Despite being an inherently ambiguous concept, player orientation can be defined as the projection (2D) of the normal vector placed in the center of the upper-torso of players (3D). This research presents a novel technique to obtain player orientation from monocular video recordings by mapping pose parts (shoulders and hips) in a 2D field by combining OpenPose with a super-resolution network, and merging the obtained estimation with contextual information (ball position). Results have been validated with players-held EPTS devices, obtaining a median error of 27 degrees/player. Moreover, three novel types of orientation maps are proposed in order to make raw orientation data easy to visualize and understand, thus allowing further analysis at team- or player-level.

该研究针对足球运动员的身体定位这一尚未深入探讨的领域，提出了一种新颖的技术，可结合OpenPose和超分辨率网络等技术从单目视频录像中获取球员身体定向，进而生成可视化的定向数据，替补了目前定位方面的空白。

总是看向场地的亮面：融合姿势和背景数据来估计足球运动员的方向