Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images

by   Vinkle Srivastav, et al.
Université de Strasbourg

Human pose estimation (HPE) is a key building block for developing AI-based context-aware systems inside the operating room (OR). The 24/7 use of images coming from cameras mounted on the OR ceiling can however raise concerns for privacy, even in the case of depth images captured by RGB-D sensors. Being able to solely use low-resolution privacy-preserving images would address these concerns and help scale up the computer-assisted approaches that rely on such data to a larger number of ORs. In this paper, we introduce the problem of HPE on low-resolution depth images and propose an end-to-end solution that integrates a multi-scale super-resolution network with a 2D human pose estimation network. By exploiting intermediate feature-maps generated at different super-resolution, our approach achieves body pose results on low-resolution images (of size 64x48) that are on par with those of an approach trained and tested on full resolution images (of size 640x480).


page 2

page 4

page 8

page 10

page 11

page 12

page 13

page 14


Super Resolution in Human Pose Estimation: Pixelated Poses to a Resolution Result?

The results obtained from state of the art human pose estimation (HPE) m...

Learning Privacy-Preserving Optics for Human Pose Estimation

The widespread use of always-connected digital cameras in our everyday l...

SSP-Net: Scalable Sequential Pyramid Networks for Real-Time 3D Human Pose Regression

In this paper we propose a highly scalable convolutional neural network,...

Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images

Computer-vision hospital systems can greatly assist healthcare workers a...

3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning

3D human shape and pose estimation from monocular images has been an act...

How low can you go? Privacy-preserving people detection with an omni-directional camera

In this work, we use a ceiling-mounted omni-directional camera to detect...

Privacy-Preserving In-Bed Pose Monitoring: A Fusion and Reconstruction Study

Recently, in-bed human pose estimation has attracted the interest of res...

Please sign up or login with your details

Forgot password? Click here to reset