Name
Title | ||
|---|---|---|
A Hybrid Background Subtraction Method with Background and Foreground Candidates Detection |
Abstract | ||
|---|---|---|
Background subtraction for motion detection is often used in video surveillance systems. However, difficulties in bootstrapping restrict its development. This article proposes a novel hybrid background subtraction technique to solve this problem. For performance improvement of background subtraction, the proposed technique not only quickly initializes the background model but also eliminates unnecessary regions containing only background pixels in the object detection process. Furthermore, an embodiment based on the proposed technique is also presented. Experimental results verify that the proposed technique allows for reduced execution time as well as improvement of performance as evaluated by Recall, Precision, F1, and Similarity metrics when used with state-of-the-art background subtraction methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2746409 | ACM Transactions on Intelligent Systems and Technology |
Keywords | Field | DocType |
Design,Algorithms,Performance,Video surveillance,motion detection,background subtraction,background candidates,foreground candidates | Background subtraction,Object detection,Computer vision,Motion detection,Computer science,Bootstrapping,Execution time,Pixel,Artificial intelligence,restrict,Performance improvement | Journal |
Volume | Issue | ISSN |
7 | 1 | 2157-6904 |
Citations | PageRank | References |
18 | 0.58 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fan-Chieh Cheng | 1 | 289 | 18.49 |
| Bo-Hao Chen | 2 | 244 | 21.00 |
| Shih-Chia Huang | 3 | 657 | 42.31 |