An Adaptive Background Subtraction Method Based on Kernel Density Estimation
In this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the le...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2012-09-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/9/12279 |
| _version_ | 1811278949673598976 |
|---|---|
| author | Mignon Park Jeisung Lee |
| author_facet | Mignon Park Jeisung Lee |
| author_sort | Mignon Park |
| collection | DOAJ |
| description | In this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the learning rate according to the situations. We apply an adaptive threshold method based on image changes to effectively subtract the dynamic backgrounds. The devised scheme allows the proposed method to automatically adapt to various environments and effectively extract the foreground. The method presented here exhibits good performance and is suitable for dynamic background environments. The algorithm is tested on various video sequences and compared with other state-of-the-art background subtraction methods so as to verify its performance. |
| first_indexed | 2024-04-13T00:44:56Z |
| format | Article |
| id | doaj.art-dc00ddd38480405089cddea8853392c4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:44:56Z |
| publishDate | 2012-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dc00ddd38480405089cddea8853392c42022-12-22T03:10:02ZengMDPI AGSensors1424-82202012-09-01129122791230010.3390/s120912279An Adaptive Background Subtraction Method Based on Kernel Density EstimationMignon ParkJeisung LeeIn this paper, a pixel-based background modeling method, which uses nonparametric kernel density estimation, is proposed. To reduce the burden of image storage, we modify the original KDE method by using the first frame to initialize it and update it subsequently at every frame by controlling the learning rate according to the situations. We apply an adaptive threshold method based on image changes to effectively subtract the dynamic backgrounds. The devised scheme allows the proposed method to automatically adapt to various environments and effectively extract the foreground. The method presented here exhibits good performance and is suitable for dynamic background environments. The algorithm is tested on various video sequences and compared with other state-of-the-art background subtraction methods so as to verify its performance.http://www.mdpi.com/1424-8220/12/9/12279background subtractionkernel density estimationvideo surveillanceadaptive background estimation |
| spellingShingle | Mignon Park Jeisung Lee An Adaptive Background Subtraction Method Based on Kernel Density Estimation Sensors background subtraction kernel density estimation video surveillance adaptive background estimation |
| title | An Adaptive Background Subtraction Method Based on Kernel Density Estimation |
| title_full | An Adaptive Background Subtraction Method Based on Kernel Density Estimation |
| title_fullStr | An Adaptive Background Subtraction Method Based on Kernel Density Estimation |
| title_full_unstemmed | An Adaptive Background Subtraction Method Based on Kernel Density Estimation |
| title_short | An Adaptive Background Subtraction Method Based on Kernel Density Estimation |
| title_sort | adaptive background subtraction method based on kernel density estimation |
| topic | background subtraction kernel density estimation video surveillance adaptive background estimation |
| url | http://www.mdpi.com/1424-8220/12/9/12279 |
| work_keys_str_mv | AT mignonpark anadaptivebackgroundsubtractionmethodbasedonkerneldensityestimation AT jeisunglee anadaptivebackgroundsubtractionmethodbasedonkerneldensityestimation AT mignonpark adaptivebackgroundsubtractionmethodbasedonkerneldensityestimation AT jeisunglee adaptivebackgroundsubtractionmethodbasedonkerneldensityestimation |