Name
Abstract | ||
|---|---|---|
Fast and accurate moving object segmentation in dynamic scenes is the first step in many computer vision applications. In this paper, we propose a new background modeling method for moving object segmentation based on dynamic matrix and spatio-temporal analyses of scenes. Our method copes with some challenges related to this field. A new algorithm is proposed to detect and remove cast shadow. A comparative study by quantitative evaluations shows that the proposed approach can detect foreground robustly and accurately from videos recorded by a static camera and which include several constraints. A Highway Control and Management System called RoadGuard is proposed to show the robustness of our method. In fact, our system has the ability to control highway by detecting strange events that can happen like vehicles suddenly stopped in roads, parked vehicles in emergency zones or even illegal conduct such as going out from the road. Moreover, RoadGuard is capable of managing highways by saving information about the date and time of overloaded roads. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s11042-011-0935-6 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Background modeling,Cast shadow detection and removal,Moving object detection | Computer vision,Shadow,Pattern recognition,Quantitative Evaluations,Segmentation,Matrix (mathematics),Computer science,Robustness (computer science),Artificial intelligence,Management system | Journal |
Volume | Issue | ISSN |
63 | 3 | 1380-7501 |
Citations | PageRank | References |
6 | 0.48 | 30 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohamed Hammami | 1 | 181 | 30.54 |
| Salma Kammoun Jarraya | 2 | 13 | 5.36 |
| hanene benabdallah | 3 | 65 | 13.16 |