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

arXiv: https://arxiv.org/abs/1811.09950 · HTML: https://mlsanity.com/paper/1811.09950/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Nov 2018.

## Built on by (most cited first, 15 of 15)

- [SPAct: Self-supervised Privacy Preservation for Action Recognition](https://mlsanity.com/paper/2203.15205/) (2022)
- [STPrivacy: Spatio-Temporal Privacy-Preserving Action Recognition](https://mlsanity.com/paper/2301.03046/) (2023)
- [Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition](https://mlsanity.com/paper/2306.11546/) (2023)
- [Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the operating room](https://mlsanity.com/paper/2108.11801/) (2021)
- [SoundCam: A Dataset for Finding Humans Using Room Acoustics](https://mlsanity.com/paper/2311.03517/) (2023)
- [A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring](https://mlsanity.com/paper/2105.02960/) (2021)
- [Balancing Privacy and Action Performance: A Penalty-Driven Approach to Image Anonymization](https://mlsanity.com/paper/2504.14301/) (2025)
- [Activity Recognition on Avatar-Anonymized Datasets with Masked Differential Privacy](https://mlsanity.com/paper/2410.17098/) (2024)
- [Leveraging Computer Vision in the Intensive Care Unit (ICU) for Examining Visitation and Mobility](https://mlsanity.com/paper/2403.06322/) (2024)
- [From Pixels to Privacy: Temporally Consistent Video Anonymization via Token Pruning for Privacy Preserving Action Recognition](https://mlsanity.com/paper/2603.26336/) (2026)
- [Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data](https://mlsanity.com/paper/2309.15635/) (2023)
- [StegaVAR: Privacy-Preserving Video Action Recognition via Steganographic Domain Analysis](https://mlsanity.com/paper/2512.12586/) (2025)
- [On the Design of Privacy-Aware Cameras: a Study on Deep Neural Networks](https://mlsanity.com/paper/2208.11372/) (2022)
- [TouchMap-OR: Multi-View 3D Mapping of Hand-Surface Contacts](https://mlsanity.com/paper/2605.17638/) (2026)
- [Bit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation](https://mlsanity.com/paper/2606.29417/) (2026)

## Abstract (arXiv)

Computer-vision hospital systems can greatly assist healthcare workers and improve medical facility treatment, but often face patient resistance due to the perceived intrusiveness and violation of privacy associated with visual surveillance. We downsample video frames to extremely low resolutions to degrade private information from surveillance videos. We measure the amount of activity-recognition information retained in low resolution depth images, and also apply a privately-trained DCSCN super-resolution model to enhance the utility of our images. We implement our techniques with two actual healthcare-surveillance scenarios, hand-hygiene compliance and ICU activity-logging, and show that our privacy-preserving techniques preserve enough information for realistic healthcare tasks.