Abstract
This paper proposes a new framework for video surveillance systems for crime prevention. The main purpose of this framework is to help provide reasonable and stable solutions for automated video surveillance systems in a collaborative way. This framework is characterized by a verification process using crowdsourcing after the image analysis process: automated image analyzer detects as many suspicious events as possible followed by filtering process using human intelligence, to achieve both high recall and high precision rates. Here we describe the basic mechanisms for collaboration between camera devices, data stores, image analyzers and surveillance crowds.
Original language | English |
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Title of host publication | Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW |
Publisher | Association for Computing Machinery |
Pages | 393-396 |
Number of pages | 4 |
Volume | 26-February-2016 |
ISBN (Print) | 9781450339506 |
DOIs | |
Publication status | Published - 2016 Feb 27 |
Event | 19th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States Duration: 2016 Feb 26 → 2016 Mar 2 |
Other
Other | 19th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2016 |
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Country | United States |
City | San Francisco |
Period | 16/2/26 → 16/3/2 |
Keywords
- Collaborative video surveillance
- Crowdsourcing
- Framework
ASJC Scopus subject areas
- Software
- Computer Networks and Communications
- Human-Computer Interaction