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.

本文介绍了一种基于标记的多视角脊柱跟踪方法，特别适用于体育运动中所需的移动，用于脊柱形状的优化，通过线性规划和马尔可夫随机场进行三维推理，与现有技术相比，实验结果表明我们的系统具有高精度和标记密度，对遮挡也比较鲁棒，能够捕捉快速运动。