Abstract
We propose a new method for background modeling. Our method is based on the two complementary approaches. One uses the probability density function (PDF) to approximatebackground model. The PDF is estimated non-parametrically by using Parzen density estimation. Then, foreground object is detected based on the estimated PDF. The method is based on the evaluation of the local texture at pixel-level resolution which reduces the effects of variations in lighting. Fusing those approachs realizes robust object detection under varying illumination. Several experiments show the effectiveness of our approach.
Original language | English |
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Pages (from-to) | 21-31 |
Number of pages | 11 |
Journal | Progress in Informatics |
Issue number | 7 |
DOIs | |
Publication status | Published - Mar 2010 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Library and Information Sciences