| Paper: | WA-L5.6 |
| Session: | Video Surveillance II |
| Time: | Wednesday, September 19, 11:50 - 12:10 |
| Presentation: |
Lecture
|
| Title: |
REAL-TIME MOVING OBJECT CLASSIFICATION WITH AUTOMATIC SCENE DIVISION |
| Authors: |
Zhaoxiang Zhang; Chinese Academy of Sciences | | |
| | Yinghao Cai; Chinese Academy of Sciences | | |
| | Kaiqi Huang; Chinese Academy of Sciences | | |
| | Tieniu Tan; Chinese Academy of Sciences | | |
| Abstract: |
We address the problem of moving object classification. Our aim is to classify moving objects into pedestrians, bicycles and vehicles from traffic scene videos. Instead of supervised learning and manual labeling of large training samples, our classifiers are initialized and refined online automatically. With efficient features extracted and organized, the approach can be real-time and achieve high classification accuracy. Once the view or scene changes detected, the algorithm can automatically refine the classifiers and adapt them to new environments. Experimental results demonstrate the effectiveness and robustness of the proposed approach. |
