In this work, we present a marker-based multi-view spine tracking method that is specifically adjusted to the requirements for movements in sports. A maximal focus is on the accurate detection of markers and fast usage of the system. For this task, we take advantage of the prior knowledge of the arrangement of dots in perforated kinesiology tape. We detect the tape and its dots using a Mask R-CNN and a blob detector. Here, we can focus on detection only while skipping any image-based feature encoding or matching. We conduct a reasoning in 3D by a linear program and Markov random fields, in which the structure of the kinesiology tape is modeled and the shape of the spine is optimized. In comparison to state-of-the-art systems, we demonstrate that our system achieves high precision and marker density, is robust against occlusions, and capable of capturing fast movements.

翻译：本研究提出一种基于标记的多视角脊柱追踪方法，该方法专门针对体育运动中的动作需求进行了调整，重点在于实现标记点的精确检测与系统的快速部署。为此，我们利用穿孔肌内效贴中圆点排列的先验知识，通过Mask R-CNN与斑点检测器识别贴布及其圆点。在此过程中，我们仅专注于检测环节，跳过任何基于图像的特征编码或匹配步骤。通过线性规划与马尔可夫随机场进行三维推理，对肌内效贴的结构进行建模并优化脊柱形态。与现有先进系统相比，我们的系统具有高精度、高标记点密度、抗遮挡能力强以及能够捕捉快速运动的优势。