Reducing False Triggers In Surveillance Systems Using Sensor Fusion
(2017) In Master's Theses in Mathematical Sciences FMA820 20162Mathematics (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?
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8905482
- author
- Boström, Madeleine LU and Claesson, Tobias LU
- supervisor
- organization
- alternative title
- Falsklarmsreducering i övervakningssystem med hjälp av sensorfusion
- course
- FMA820 20162
- year
- 2017
- 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}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{Reducing False Triggers In Surveillance Systems Using Sensor Fusion}}, year = {{2017}}, }