# SecurePose: Automated Face Blurring and Human Movement Kinematics Extraction from Videos Recorded in Clinical Settings

arXiv: https://arxiv.org/abs/2402.14143 · HTML: https://mlsanity.com/paper/2402.14143/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 95 references that are in the map.
- First posted on arXiv 21 Feb 2024.

## Builds on (most cited first, 17 of 17)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [SSD: Single Shot MultiBox Detector](https://mlsanity.com/paper/1512.02325/) (2015)
- [YOLOv3: An Incremental Improvement](https://mlsanity.com/paper/1804.02767/) (2018)
- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1611.08050/) (2016)
- [Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks](https://mlsanity.com/paper/1604.02878/) (2016)
- [DensePose: Dense Human Pose Estimation In The Wild](https://mlsanity.com/paper/1802.00434/) (2018)
- [WIDER FACE: A Face Detection Benchmark](https://mlsanity.com/paper/1511.06523/) (2015)
- [S3FD: Single Shot Scale-invariant Face Detector](https://mlsanity.com/paper/1708.05237/) (2017)
- [Finding Tiny Faces](https://mlsanity.com/paper/1612.04402/) (2016)
- [Deep Dual Consecutive Network for Human Pose Estimation](https://mlsanity.com/paper/2103.07254/) (2021)
- [Max-Margin Object Detection](https://mlsanity.com/paper/1502.00046/) (2015)
- [Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation](https://mlsanity.com/paper/2003.00813/) (2020)
- [Faceness-Net: Face Detection through Deep Facial Part Responses](https://mlsanity.com/paper/1701.08393/) (2017)
- [Convolutional STN for Weakly Supervised Object Localization](https://mlsanity.com/paper/1912.01522/) (2019)
- [A Multi-Scale Cascade Fully Convolutional Network Face Detector](https://mlsanity.com/paper/1609.03536/) (2016)
- [A Deep Pyramid Deformable Part Model for Face Detection](https://mlsanity.com/paper/1508.04389/) (2015)

## Abstract (arXiv)

Movement disorder diagnosis often relies on expert evaluation of patient videos, but sharing these videos poses privacy risks. Current methods for de-identifying videos, such as blurring faces, are often manual, inconsistent, or inaccurate. Furthermore, these methods can compromise objective kinematic analysis - a crucial component of diagnosis. To address these challenges, we developed SecurePose, an open-source software that simultaneously provides reliable de-identification and automated kinematic extraction from videos recorded in clinic settings using smartphones/tablets. SecurePose utilizes pose estimation (using OpenPose) to extract full body kinematics, track individuals, identify the patient, and then accurately blur faces in the videos. We validated SecurePose on gait videos recorded in outpatient clinic visits of 116 children with cerebral palsy, assessing both the accuracy of its de-identification compared to the ground truth (manual blurring) and the reliability of the intermediate steps of kinematics extraction. Results demonstrate that SecurePose outperformed six existing methods in automated face detection and achieved comparable accuracy to robust manual blurring, but in significantly less time (91.08% faster). Ten experienced researchers also confirmed SecurePose's usability via System Usability Scale scores. These findings validate SecurePose as a practical and effective tool for protecting patient privacy while enabling accurate kinematics extraction in clinical settings.