Name
Abstract | ||
|---|---|---|
This paper presents a novel approach to background subtraction which aims to extract moving objects in video stream. To this end, a novel background model is proposed by using both working backgrounds and candidate backgrounds, which can be transferred to each other according to an adaptive mechanism. The input image (video frame) is compared and evaluated with these dual-class backgrounds (DCB) to detect foreground objects. Furthermore, for robust background modeling a novel background updating scheme is proposed based on the life-value which represents the existing time of a background sample, and the access-time which represents the number of valid visits of a background sample. Experiments on a standard dataset demonstrated the effectiveness and robustness of the proposed approach by comparing it with the previous typical background subtraction techniques. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICARCV.2016.7838754 | 2016 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV) |
Keywords | Field | DocType |
background subtraction, working backgrounds, candidate backgrounds, dual-class backgrounds | Background subtraction,Computer vision,Computer science,Euclidean distance,Impedance matching,Robustness (computer science),Vehicle dynamics,Artificial intelligence | Conference |
ISSN | Citations | PageRank |
2474-2953 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wang Bingshu | 1 | 1 | 0.69 |
| Zhu Wenqian | 2 | 1 | 1.03 |
| Tang Song | 3 | 0 | 0.34 |
| Zhao Yong | 4 | 90 | 14.85 |
| Wenbin Zou | 5 | 268 | 19.75 |