Finding Field of View Overlap by Motion Analysis
(2017) In Master's Theses in Mathematical Sciences FMA820 20171Mathematics (Faculty of Engineering)
- Abstract
- Network cameras has in the recent years become more powerful. Each camera is independent and has its own surveillance task. It is reasonable that network cameras in the future should cooperate together to increase surveillance effectiveness. There is a need to find cameras sharing the same field of view in order for an operator to switch perspective. This thesis investigates how multiple network cameras can cooperate by finding the shared field of view between cameras. With the shared field of view, we implement an additional knowledge above system of network cameras and new use cases arises. Our method consist of applying a grid of cells on each camera's video stream and study movement detection. We gather contradicting proof of... (More)
- Network cameras has in the recent years become more powerful. Each camera is independent and has its own surveillance task. It is reasonable that network cameras in the future should cooperate together to increase surveillance effectiveness. There is a need to find cameras sharing the same field of view in order for an operator to switch perspective. This thesis investigates how multiple network cameras can cooperate by finding the shared field of view between cameras. With the shared field of view, we implement an additional knowledge above system of network cameras and new use cases arises. Our method consist of applying a grid of cells on each camera's video stream and study movement detection. We gather contradicting proof of connectedness between each cell in the whole network of cameras. Our method avoids problems with feature detection such as different perspectives or image quality. We found that our method works with promising results and we can find shared field of view between cameras. There is a limitation in memory of storing all cells and we can only find overlap in regions with movement. This field has not been researched so much, making evaluation hard, as many approaches focuses on feature detection. (Less)
- Popular Abstract
- Network cameras has significantly increased in the recent years. Each camera is independent and its monitoring task can easily be remotely altered. This work focuses on increasing effectiveness of a system of cameras by adding additional knowledge on top of the system and by utilizing multiple cameras when a shared field of view has been found.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8926463
- author
- Sydvart, Fredrik LU and Altvall, Hampus LU
- supervisor
- organization
- course
- FMA820 20171
- year
- 2017
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- surveillance network, network cameras, shared field of view, camera overlap, motion detection
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUTFMA-3332-2017
- ISSN
- 1404-6342
- other publication id
- 2017:E62
- language
- English
- id
- 8926463
- date added to LUP
- 2017-12-01 15:33:29
- date last changed
- 2018-10-11 16:20:05
@misc{8926463, abstract = {{Network cameras has in the recent years become more powerful. Each camera is independent and has its own surveillance task. It is reasonable that network cameras in the future should cooperate together to increase surveillance effectiveness. There is a need to find cameras sharing the same field of view in order for an operator to switch perspective. This thesis investigates how multiple network cameras can cooperate by finding the shared field of view between cameras. With the shared field of view, we implement an additional knowledge above system of network cameras and new use cases arises. Our method consist of applying a grid of cells on each camera's video stream and study movement detection. We gather contradicting proof of connectedness between each cell in the whole network of cameras. Our method avoids problems with feature detection such as different perspectives or image quality. We found that our method works with promising results and we can find shared field of view between cameras. There is a limitation in memory of storing all cells and we can only find overlap in regions with movement. This field has not been researched so much, making evaluation hard, as many approaches focuses on feature detection.}}, author = {{Sydvart, Fredrik and Altvall, Hampus}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{Finding Field of View Overlap by Motion Analysis}}, year = {{2017}}, }