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Reducing False Triggers In Surveillance Systems Using Sensor Fusion

Boström, Madeleine LU and Claesson, Tobias LU (2017) In Master's Theses in Mathematical Sciences FMA820 20162
Mathematics (Faculty of Engineering)
Abstract
Sensor fusion has been widely adopted in the last couple of years, especially in the automobile industry. Their main goal is to gain a more robust system and increase security by e.g. predicting and preventing collisions.

Surveillance systems, based on video motion detection, face similar issues by having numerous problems with false triggers, particularly when there are big variations in the lighting of the scene, e.g. shadows or light beams. To address this issue, the effect of adding a radar sensor, whilst the video system is used as a black box, is investigated.

There exists a presentiment that the amount of detections that are identified should not decrease noteworthy, as the two different systems complement each other. The... (More)
Sensor fusion has been widely adopted in the last couple of years, especially in the automobile industry. Their main goal is to gain a more robust system and increase security by e.g. predicting and preventing collisions.

Surveillance systems, based on video motion detection, face similar issues by having numerous problems with false triggers, particularly when there are big variations in the lighting of the scene, e.g. shadows or light beams. To address this issue, the effect of adding a radar sensor, whilst the video system is used as a black box, is investigated.

There exists a presentiment that the amount of detections that are identified should not decrease noteworthy, as the two different systems complement each other. The validation is not necessarily identical with reality, however it is a clear indication that sensor fusion is more reliable than using only video motion detection. (Less)
Popular Abstract
To be able to rely on your surveillance system is of great importance. If you invest in a surveillance system to guard your premises, you want to be certain that the system detects all trespassers. However, if there are too many false alarms it might create a ''boy who cried wolf'' situation and you can become reluctant to react. Could a video surveillance system be more reliable when it's combined with a radar sensor?
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author
Boström, Madeleine LU and Claesson, Tobias LU
supervisor
organization
alternative title
Falsklarmsreducering i övervakningssystem med hjälp av sensorfusion
course
FMA820 20162
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Sensor fusion, Information fusion, Radar, Video, Motion detection, Surveillance system
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFMA-3313-2017
ISSN
1404-6342
other publication id
2017:E10
language
English
id
8905482
date added to LUP
2017-05-16 17:54:59
date last changed
2017-06-10 04:09:57
@misc{8905482,
  abstract     = {Sensor fusion has been widely adopted in the last couple of years, especially in the automobile industry. Their main goal is to gain a more robust system and increase security by e.g. predicting and preventing collisions.
 
Surveillance systems, based on video motion detection, face similar issues by having numerous problems with false triggers, particularly when there are big variations in the lighting of the scene, e.g. shadows or light beams. To address this issue, the effect of adding a radar sensor, whilst the video system is used as a black box, is investigated.
 
There exists a presentiment that the amount of detections that are identified should not decrease noteworthy, as the two different systems complement each other. The validation is not necessarily identical with reality, however it is a clear indication that sensor fusion is more reliable than using only video motion detection.},
  author       = {Boström, Madeleine and Claesson, Tobias},
  issn         = {1404-6342},
  keyword      = {Sensor fusion,Information fusion,Radar,Video,Motion detection,Surveillance system},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master's Theses in Mathematical Sciences},
  title        = {Reducing False Triggers In Surveillance Systems Using Sensor Fusion},
  year         = {2017},
}