Title
A fast and accurate motion detection algorithm for embedded systems
Abstract
Last decade witnessed the rapid development of Wireless Sensor Networks. More recently, the availability of inexpensive hardware such as CMOS cameras and microphones that are able to ubiquitously capture multimedia content from the environment has fostered the development ofWireless Multimedia Sensor Networks (WMSNs). There is a wide range of applications that are using Wireless Multimedia Sensor Networks, including Indoor Surveillance Systems. Nearly all surveillance systems start with a motion detection algorithm. After detection of motion in an image, either the motion areas are sent to another algorithm for more processing or an alarm is sent to the base station informing that there is motion in the environment. In this paper, we proposed a new motion detection algorithm, which is specifically designed for scenarios with no constant movement in the background. Our tests using Goyette's datasets show that, our proposed algorithm achieved a 97% accuracy with an average execution time of 48ms for QVGA images on ARM9 architecture, and thus outperformed the two currently available methods.
Year
DOI
Venue
2013
10.1109/SIU.2013.6531461
Signal Processing and Communications Applications Conference
Keywords
Field
DocType
embedded systems,image motion analysis,object detection,video signal processing,ARM9 architecture,Goyette dataset,QVGA images,embedded systems,motion detection algorithm,no constant movement scenario,Indoor Surveillance Systems,Motion Detection,Wireless Multimedia Sensor Networks
Base station,ARM9,Computer science,Real-time computing,Artificial intelligence,Object detection,Computer vision,Motion detection,ALARM,Algorithm,CMOS,Wireless sensor network,Constant movement,Embedded system
Conference
ISSN
ISBN
Citations 
2165-0608
978-1-4673-5561-2
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
N. Cihan Camgoz100.34
Z. Cihan Taysi2466.78
M. Amaç Güvensan352.30
M. Elif Karsligil47313.69
A. Gökhan Yavuz501.69