A SVM kernel for classifying partially occluded images
We propose a novel SVM (Support Vector Machine) kernel for classifying partially occluded images in the process of video tracking. The SVM kernel (called Bhattacharyya kernel) is derived from Bhattacharyya coefficient. In our study, the validity of Bhattacharyya kernel is proven. We use kernel densi...
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| creator | Risheng Han Hui Ding Guangxue Yue |
| description | We propose a novel SVM (Support Vector Machine) kernel for classifying partially occluded images in the process of video tracking. The SVM kernel (called Bhattacharyya kernel) is derived from Bhattacharyya coefficient. In our study, the validity of Bhattacharyya kernel is proven. We use kernel density estimation of histogram as SVM's feature space. Experiments show the SVM based on Bhattacharyya kernel can keep high classification accuracy when occlusion or clutter of peripheral pixels appears. Bhattacharyya kernel can be generalized easily when using other features. |
| doi_str_mv | 10.1109/ICCASM.2010.5622641 |
| format | Conference Proceeding |
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| identifier | ISSN: 2161-9069 |
| ispartof | 2010 International Conference on Computer Application and System Modeling (ICCASM 2010), 2010, Vol.10, p.V10-615-V10-618 |
| issn | 2161-9069 |
| language | eng |
| recordid | cdi_ieee_primary_5622641 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Bhattacharyya Kernel Estimation Kernel density estimation Support vector machines SVM |
| title | A SVM kernel for classifying partially occluded images |
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