Name
Title | ||
|---|---|---|
Fast Background Subtraction Based on a Multilayer Codebook Model for Moving Object Detection |
Abstract | ||
|---|---|---|
Moving object detection is an important and fundamental step for intelligent video surveillance systems because it provides a focus of attention for post-processing. A multilayer codebook-based background subtraction (MCBS) model is proposed for video sequences to detect moving objects. Combining the multilayer block-based strategy and the adaptive feature extraction from blocks of various sizes, the proposed method can remove most of the nonstationary (dynamic) background and significantly increase the processing efficiency. Moreover, the pixel-based classification is adopted for refining the results from the block-based background subtraction, which can further classify pixels as foreground, shadows, and highlights. As a result, the proposed scheme can provide a high precision and efficient processing speed to meet the requirements of real-time moving object detection. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TCSVT.2013.2269011 | IEEE Transactions on Circuits and Systems for Video Technology |
Keywords | Field | DocType |
feature extraction,image classification,background subtraction | Background subtraction,Computer vision,Object detection,Pattern recognition,Computer science,Feature extraction,Video tracking,Artificial intelligence,Pixel,Contextual image classification,Codebook | Journal |
Volume | Issue | ISSN |
23 | 10 | 1051-8215 |
Citations | PageRank | References |
44 | 1.16 | 12 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing-Ming Guo | 1 | 830 | 77.60 |
| Chih-hsien Hsia | 2 | 222 | 24.24 |
| Yun-Fu Liu | 3 | 277 | 19.65 |
| Min-Hsiung Shih | 4 | 85 | 3.30 |
| Cheng-Hsin Chang | 5 | 44 | 1.16 |
| Jingyu Wu | 6 | 51 | 2.38 |