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Area Based Alarm System using 3D Cameras

Kåhrström, Jonatan and Gustafsson, Daniel LU (2012) In Master's Theses in Mathematical Sciences FMA820 20122
Mathematics (Faculty of Technology) and Numerical Analysis
Abstract
Depth map cameras provide new ways of designing surveillance systems. In this thesis we evaluate three different cameras from two different depth sensor techniques, and propose a complete method for detecting thefts over a counter in a retail environment. Our algorithm covers pre-processing with noise reduction and background segmentation using the reflected signals amplitude as a confidence measurement. A plane is fitted both to the 3D points of the top of the retail counter as well as to the 3D points on the side (cashiers side) of the retail counter. The algorithm determines which foreground pixels are on the wrong side of both these planes. By running this result through a few methods to improve rigidity, we show that it is possible to... (More)
Depth map cameras provide new ways of designing surveillance systems. In this thesis we evaluate three different cameras from two different depth sensor techniques, and propose a complete method for detecting thefts over a counter in a retail environment. Our algorithm covers pre-processing with noise reduction and background segmentation using the reflected signals amplitude as a confidence measurement. A plane is fitted both to the 3D points of the top of the retail counter as well as to the 3D points on the side (cashiers side) of the retail counter. The algorithm determines which foreground pixels are on the wrong side of both these planes. By running this result through a few methods to improve rigidity, we show that it is possible to detect thefts with a very high detection rate and low false positive rate. Finally we present the results from our testing of different versions on a database of activities with known ground-truth (theft/no theft). (Less)
Please use this url to cite or link to this publication:
author
Kåhrström, Jonatan and Gustafsson, Daniel LU
supervisor
organization
alternative title
Områdesbaserat alarm med hjälp av 3D kameror
course
FMA820 20122
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Image Analysis, Surveillance, 3D cameras, Time of Flight, Structured Light
publication/series
Master's Theses in Mathematical Sciences
report number
LUTFMA-3233-2012
ISSN
1404-6342
other publication id
2012: E39
language
English
id
3346589
date added to LUP
2013-09-20 12:24:01
date last changed
2013-09-20 12:24:01
@misc{3346589,
  abstract     = {Depth map cameras provide new ways of designing surveillance systems. In this thesis we evaluate three different cameras from two different depth sensor techniques, and propose a complete method for detecting thefts over a counter in a retail environment. Our algorithm covers pre-processing with noise reduction and background segmentation using the reflected signals amplitude as a confidence measurement. A plane is fitted both to the 3D points of the top of the retail counter as well as to the 3D points on the side (cashiers side) of the retail counter. The algorithm determines which foreground pixels are on the wrong side of both these planes. By running this result through a few methods to improve rigidity, we show that it is possible to detect thefts with a very high detection rate and low false positive rate. Finally we present the results from our testing of different versions on a database of activities with known ground-truth (theft/no theft).},
  author       = {Kåhrström, Jonatan and Gustafsson, Daniel},
  issn         = {1404-6342},
  keyword      = {Image Analysis,Surveillance,3D cameras,Time of Flight,Structured Light},
  language     = {eng},
  note         = {Student Paper},
  series       = {Master's Theses in Mathematical Sciences},
  title        = {Area Based Alarm System using 3D Cameras},
  year         = {2012},
}