Title
Automated and coupled services of advanced smart surveillance systems toward green IT: tracking, retrieval and digital evidence
Abstract
Green Security is a new research field defining and investigating security solutions using an energy-aware perspective. Growing efforts and interests for an intelligent or smart surveillance system which is capable of automatically detecting and tracking target objects is in the spotlight in the security community. So far, these technologies are mainly aimed at single camera applications and are evolving with the demand for wide-area surveillance systems currently. However, the tracking techniques used on a single camera have limitations in providing effective crime prevention and countermeasures when an incident occurs since an object is not linked to other cameras. In addition, the use of multi-camera systems for wide-area surveillance not only produces large amounts of video data to be stored, but also have more technical requirements in the interrelation between cameras or server. It require a considerable amount of time, manpower and energy in multi-camera tracking and back-tracking of objects. Therefore, we propose the advanced smart surveillance system for wide-areas which is capable of the automated tracking and retrieval of target object and digital evidence-video collection. Furthermore, we considered the multiple-camera environment with non-overlapping views which includes more constraint conditions by various light changes. This system enables real-time object tracking, fast post-retrieval and selective digital evidence collection with economy of time, manpower, memory devices, and energy consumption. Also, this system is more energy-efficient since our schemes are organically connected to each other.
Year
DOI
Venue
2014
10.1007/s11227-014-1164-3
The Journal of Supercomputing
Keywords
Field
DocType
Surveillance system,Video surveillance,Object tracking,Video retrieval,Digital evidence
Countermeasure,Green computing,Computer science,Smart camera,Digital evidence,Video tracking,Energy consumption,Distributed computing,Security community,Crime prevention
Journal
Volume
Issue
ISSN
69
3
0920-8542
Citations 
PageRank 
References 
1
0.35
15
Authors
4
Name
Order
Citations
PageRank
Su-Wan Park1342.89
Deokgyu Lee26112.70
Jongwook Han34915.05
Jeongnyeo Kim45316.85