In this study, primary steps of a visual surveillance system are presented: moving
object detection and tracking of these moving objects. Background subtraction has
been performed to detect the moving objects in the video, which has been taken
from a static camera. Four methods, frame differencing, running (moving)
average, eigenbackground subtraction and mixture of Gaussians, have been used
in the background subtraction process. After background subtraction, using some
additional operations, such as morphological operations and connected component
analysis, the objects to be tracked have been acquired. While tracking the moving
objects, active contour models (snakes) has been used as one of the approaches. In
addition to this method / Kalman tracker and mean-shift tracker are other
approaches which have been utilized. A new approach has been proposed for the
problem of tracking multiple targets. We have implemented this method for single
and multiple camera configurations. Multiple cameras have been used to augment
the measurements. Homography matrix has been calculated to find the correspondence between cameras. Then, measurements and tracks have been
associated by the new tracking method.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/2/12609098/index.pdf |
| Date | 01 November 2007 |
| Creators | Ergezer, Hamza |
| Contributors | Leblebicioglu, Kemal |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for METU campus |
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