# Human Spine Motion Capture using Perforated Kinesiology Tape

arXiv: https://arxiv.org/abs/2306.02930 · HTML: https://mlsanity.com/paper/2306.02930/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 23 references that are in the map.
- First posted on arXiv 5 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image](https://mlsanity.com/paper/1607.08128/) (2016)
- [Convolutional Pose Machines](https://mlsanity.com/paper/1602.00134/) (2016)
- [Slice Sampling Particle Belief Propagation](https://mlsanity.com/paper/1802.03275/) (2018)
- [Localization of Cochlear Implant Electrodes from Cone Beam Computed Tomography using Particle Belief Propagation](https://mlsanity.com/paper/2103.10434/) (2021)

## Built on by (most cited first, 2 of 2)

- [Towards Unconstrained 2D Pose Estimation of the Human Spine](https://mlsanity.com/paper/2504.08110/) (2025)
- [SIMSPINE: A Biomechanics-Aware Simulation Framework for 3D Spine Motion Annotation and Benchmarking](https://mlsanity.com/paper/2602.20792/) (2026)

## Abstract (arXiv)

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.