Effect of Face Blurring on Human Pose Estimation: Ensuring Subject Privacy for Medical and Occupational Health Applications
The face blurring of images plays a key role in protecting privacy. However, in computer vision, especially for the human pose estimation task, machine-learning models are currently trained, validated, and tested on original datasets without face blurring. Additionally, the accuracy of human pose es...
Main Authors: | Jindong Jiang, Wafa Skalli, Ali Siadat, Laurent Gajny |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/23/9376 |
Similar Items
-
Image Blur Classification and Unintentional Blur Removal
by: Rui Huang, et al.
Published: (2019-01-01) -
3D Model Based Pose Invariant Face Recognition from a Single Frontal View
by: Qinran Chen, et al.
Published: (2007-12-01) -
AUTOMATIC IDENTIFICATION METHOD OF BLURRED IMAGES
by: Mikolaj Karpinski, et al.
Published: (2015-03-01) -
APA: Adaptive Pose Alignment for Pose-Invariant Face Recognition
by: Zhanfu An, et al.
Published: (2019-01-01) -
A Unified Framework for Head Pose, Age and Gender Classification through End-to-End Face Segmentation
by: Khalil Khan, et al.
Published: (2019-06-01)