| Paper: | WP-L5.8 |
| Session: | Motion Detection and Estimation III |
| Time: | Wednesday, September 19, 17:10 - 17:30 |
| Presentation: |
Lecture
|
| Title: |
ACCURATE DYNAMIC SCENE MODEL FOR MOVING OBJECT DETECTION |
| Authors: |
Hong Yang; Huazhong University of Science and Technology | | |
| | Yihua Tan; Huazhong University of Science and Technology | | |
| | Jinwen Tian; Huazhong University of Science and Technology | | |
| | Jian Liu; Huazhong University of Science and Technology | | |
| Abstract: |
Adaptive pixel-wise Gaussian mixture model (GMM) is a popular method to model dynamic scenes viewed by a fixed camera. Whereas, it is not a trivial issue for GMM to capture the accurate mean and variance of a complex pixel. This paper presents a two-layer Gaussian mixture model (TLGMM) of dynamic scenes for moving object detection. The first layer, namely real model, deals with gradually changing pixels specially; the second layer, called on-ready model, focuses on those pixels changing significantly and irregularly. TLGMM can represent dynamic scenes more accurately and effectively. Additionally, a long term and a short term variance are taken into account to alleviate the transparent problems faced by pixel-based methods. |
