Action Recognition System Preserves Privacy in Video Sharing

Abstract

The University of Central Florida invention is a privacy preservation action recognition system. The novel training framework removes privacy information from input video in a self-supervised manner without requiring privacy labels. Visual private information leakage is an emerging key issue for the fast-growing applications of video understanding, like activity recognition. Existing approaches for mitigating privacy leakage in action recognition require privacy labels along with the action labels from the video dataset. However, annotating frames of video datasets for privacy labels is not feasible. Recent developments in self-supervised learning (SSL) have unleashed the untapped potential of unlabeled data.

Technical Details

The UCF training framework consists of three main components: anonymization function, self-supervised privacy removal branch, and action recognition branch. Researchers trained the framework using a minimax optimization strategy to minimize the action recognition cost function and maximize the privacy cost function through a contrastive self-supervised loss. By employing existing protocols of known action and privacy attributes, the framework technology achieves a competitive action-privacy trade-off to the current state-of-the-art supervised methods. In addition, the invention introduces a new protocol to evaluate the generalization of the anonymization function to novel action and privacy attributes. The self-supervised framework outperforms existing supervised methods. Code is available at https://github.com/DAVEISHAN/SPAct.

Partnering Opportunity

The research team is seeking partners for licensing, research collaboration, or both.

Stage of Development

Prototype available.

Benefit

Market Application

Publications

SPAct: Self-supervised Privacy Preservation for Action Recognition, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 18-24, 2022, New Orleans, LA, USA, 2022, pp. 20132-20141. DOI: 10.1109/CVPR52688.2022.01953.