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VR-Surv: A VR-Based Privacy Preserving Surveillance System

Doula, Achref ; Sanchez Guinea, Alejandro ; Mühlhäuser, Max (2022)
VR-Surv: A VR-Based Privacy Preserving Surveillance System.
2022 CHI Conference on Human Factors in Computing Systems. New Orleans, USA (29.04.2022-05.05.2022)
doi: 10.1145/3491101.3519645
Conference or Workshop Item, Bibliographie

Abstract

The recent advances in smart city infrastructure have provided support for a higher adoption of surveillance cameras as a mainstream crime prevention measure. However, a consequent massive deployment raises concerns about privacy issues among citizens. In this paper, we present VR-Surv, a VR-based privacy aware surveillance system for large scale urban environments. Our concept is based on conveying the semantics of the scene uniquely, without revealing the identity of the individuals or the contextual details that might violate the privacy of the entities present in the surveillance area. For this, we create a virtual replica of the areas of interest, in real-time, through the combination of procedurally generated environments and markerless motion capture models. The results of our preliminary evaluation revealed that our system successfully conceals privacy-sensitive data, while preserving the semantics of the scene. Furthermore, participants in our user study expressed higher acceptance to being surveilled through the proposed system.

Item Type: Conference or Workshop Item
Erschienen: 2022
Creators: Doula, Achref ; Sanchez Guinea, Alejandro ; Mühlhäuser, Max
Type of entry: Bibliographie
Title: VR-Surv: A VR-Based Privacy Preserving Surveillance System
Language: English
Date: 28 April 2022
Publisher: ACM
Book Title: CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
Event Title: 2022 CHI Conference on Human Factors in Computing Systems
Event Location: New Orleans, USA
Event Dates: 29.04.2022-05.05.2022
DOI: 10.1145/3491101.3519645
Abstract:

The recent advances in smart city infrastructure have provided support for a higher adoption of surveillance cameras as a mainstream crime prevention measure. However, a consequent massive deployment raises concerns about privacy issues among citizens. In this paper, we present VR-Surv, a VR-based privacy aware surveillance system for large scale urban environments. Our concept is based on conveying the semantics of the scene uniquely, without revealing the identity of the individuals or the contextual details that might violate the privacy of the entities present in the surveillance area. For this, we create a virtual replica of the areas of interest, in real-time, through the combination of procedurally generated environments and markerless motion capture models. The results of our preliminary evaluation revealed that our system successfully conceals privacy-sensitive data, while preserving the semantics of the scene. Furthermore, participants in our user study expressed higher acceptance to being surveilled through the proposed system.

Uncontrolled Keywords: Surveillance, Virtual Reality, Procedural Generation, Privacy, Motion Capture, Urban Environment, emergenCITY_INF
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Telecooperation
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Date Deposited: 07 Sep 2022 08:02
Last Modified: 27 Oct 2022 09:41
PPN: 498972011
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