An Edge-Based Approach for Robust Foreground Detection
| Autor: | Wilfried Philips, Peter Van Hese, Sebastian Gruenwedel |
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| Přispěvatelé: | Blanc-Talon, Jacques, Kleihorst, Richard, Philips, Wilfried, Popescu, Dan, Scheunders, Paul |
| Rok vydání: | 2011 |
| Předmět: |
Foreground detection
Background subtraction Technology and Engineering BACKGROUND SUBTRACTION Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Video processing video processing Edge detection TRACKING foreground detection Robustness (computer science) Computer Science::Computer Vision and Pattern Recognition foreground edge detection video surveillance Segmentation Computer vision Artificial intelligence business Smoothing |
| Zdroj: | Advanced Concepts for Intelligent Vision Systems ISBN: 9783642236860 ACIVS LECTURE NOTES IN COMPUTER SCIENCE |
| ISSN: | 0302-9743 |
| DOI: | 10.1007/978-3-642-23687-7_50 |
| Popis: | Foreground segmentation is an essential task in many image processing applications and a commonly used approach to obtain foreground objects from the background. Many techniques exist, but due to shadows and changes in illumination the segmentation of foreground objects from the background remains challenging. In this paper, we present a powerful framework for detections of moving objects in real-time video processing applications under various lighting changes. The novel approach is based on a combination of edge detection and recursive smoothing techniques.We use edge dependencies as statistical features of foreground and background regions and define the foreground as regions containing moving edges. The background is described by short- and long-term estimates. Experiments prove the robustness of our method in the presence of lighting changes in sequences compared to other widely used background subtraction techniques. |
| Databáze: | OpenAIRE |
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