Advanced Video and Signal-Based Surveillance

@INPROCEEDINGS{AVSS2011_1569430147,
  author = {Corentin Lallier and Emanuelle Reynaud and Lionel Robinault and Laure
Tougne},
  title = {{A Testing Framework for Background Subtraction Algorithms Comparison
in Intrusion Detection Context}},
  booktitle = {2011 8th IEEE International Conference on 
	Advanced Video and Signal-Based Surveillancei (AVSS)},
  year = {2011},
  pages = {6},
  month = {Aug.},
  abstract = {
Identifying objects from a video stream is a fundamental and critical task
in many computer-vision applications. A popular approach is the background
subtraction, which consists in separating foreground (moving objects) from
background. Many methodologies have been developed for automatic background
segmentation but this fundamental task is still challenging. We focus here
on a particular application of computer vision: intrusion detection in
video surveillance. We propose in this paper a multi-level methodology for
evaluating and comparing background subtraction algorithms. Three levels
are studied: first, pixel level to evaluate the accuracy of the
segmentation algorithm to attribute the right class to each pixel. Second,
image level, measuring the rate of right decision on each frame (intrusion
vs no intrusion) and finally sequence level, measuring the accordance with
the time span where objects appear. Moreover, we also propose a new
similarity measure, called D-Score, adapted to the context of intrusion
detection.
  }
}