Privacy in video surveilled spaces

Authors:
Torsten Spindler;Christoph Wartmann;Ludger Hovestadt;Daniel Roth;Luc Van Gool;Andreas Steffen
Affiliations:
ETH Zurich, Institute of Building Technology, CAAD, Wolfgang Pauli Str. 15, 8093 Zurich, Switzerland. E-mail: {spindler,wartmann,hovestadt}@arch.ethz.ch;ETH Zurich, Institute of Building Technology, CAAD, Wolfgang Pauli Str. 15, 8093 Zurich, Switzerland. E-mail: {spindler,wartmann,hovestadt}@arch.ethz.ch;ETH Zurich, Institute of Building Technology, CAAD, Wolfgang Pauli Str. 15, 8093 Zurich, Switzerland. E-mail: {spindler,wartmann,hovestadt}@arch.ethz.ch;ETH Zurich, Computer Vision Laboratory, Sternwartstrasse 7, 8092 Zurich, Switzerland. E-mail: {droth,vangool}@vision.ee.ethz.ch;ETH Zurich, Computer Vision Laboratory, Sternwartstrasse 7, 8092 Zurich, Switzerland. E-mail: {droth,vangool}@vision.ee.ethz.ch;University of Applied Sciences Rapperswil, Institute for Internet Technologies and Applications, Oberseestr. 10, 8640 Rapperswil, Switzerland. E-mail: andreas.steffen@hsr.ch
Venue:
Journal of Computer Security - Privacy, Security and Trust (PST) Technologies: Evolution and Challenges
Year:
2008

Citing 4
Cited 0

Practical Cryptography

Practical Cryptography
Bayesian Pixel Classification for Human Tracking

WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Enabling Video Privacy through Computer Vision

IEEE Security and Privacy
A survey of advances in vision-based human motion capture and analysis

Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a system prototype for self-determination and privacy enhancement in video surveilled areas by integrating computer vision and cryptographic techniques into networked building automation systems. This paper describes a system prototype and research work that has been conducted by an interdisciplinary team of researchers. People appearing in a video stream control their visibility on a per-viewer basis and can choose to allow either the real view or an obscured image to be seen. The parts of the video stream containing a person's image are protected by an AES cipher and can be sent over untrusted networks. This paper presents experimental results with the example of a meeting room scenario. We conclude with remarks on the system's usability and on the problems encountered.