Summary of Securepose: Automated Face Blurring and Human Movement Kinematics Extraction From Videos Recorded in Clinical Settings, by Rishabh Bajpai and Bhooma Aravamuthan
SecurePose: Automated Face Blurring and Human Movement Kinematics Extraction from Videos Recorded in Clinical Settings
by Rishabh Bajpai, Bhooma Aravamuthan
First submitted to arxiv on: 21 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Movement disorders are typically diagnosed by consensus-based expert evaluation of clinically acquired patient videos, but manual face blurring poses risks to patient privacy. Existing automated face blurring techniques are inconsistent or insufficient, affecting video assessment and patient privacy. To address this, we developed an open-source software called SecurePose that can both achieve reliable face blurring and automated kinematic extraction in patient videos recorded using an iPad. SecurePose extracts kinematics using OpenPose, tracks individuals, identifies the patient, and performs face blurring. We validated SecurePose on gait videos from 116 children with cerebral palsy, comparing it to six existing methods, and found that it outperformed other methods in automated face detection while achieving ceiling accuracy in less time than manual face blurring. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to diagnose a movement disorder by watching videos of patients. But sharing these videos can be risky because they contain sensitive information about the patients. To solve this problem, scientists created a special software called SecurePose that can make the videos safe and help doctors understand how the patients are moving. This software is important for many reasons, including making sure patient privacy is protected. |
