Name
Title | ||
|---|---|---|
Modelling A Background For Background Subtraction From A Sequence Of Images Formulation Of Probability Distribution Of Pixel Positions |
Abstract | ||
|---|---|---|
This paper presents a new background subtraction approach to identifying the various changes of objects in a sequence of images. A background is modelled as the probability distribution of pixel positions given intensity clusters, which is constructed from a given sequence of images. Each pixel position in a new image is then identified with either a background or a foreground, depending on its value from probability distribution of pixel positions representing a background. The presented approach is illustrated using two examples. As compared to traditional intensity-based approaches, this approach is shown to be robust to dynamic textures and various changes of illumination. |
Year | Venue | Keywords |
|---|---|---|
2011 | ICAART 2011: PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1 | Background subtraction, Foreground detection, Probability distribution of pixel positions, Intensity clusters, Kernel density estimation |
Field | DocType | Citations |
Background subtraction,Computer vision,Pattern recognition,Computer science,Probability distribution,Pixel,Artificial intelligence | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Suil Son | 1 | 0 | 1.35 |
| Young-Woon Cha | 2 | 6 | 2.82 |
| Suk I. Yoo | 3 | 80 | 30.57 |