SIFT and color feature fusion using localized maximum-margin learning for scene classification
Jianzhao Qin, N.H.C. Yung · 2011
In this paper, we proposed a method that uses localized maximum-margin learning to fuse SIFT and color features during the bags of visual words modeling process for eventual scene classification. It offers a more flexible way in fusing these features through determining the similarity-metric locally by localized maximum-margin learning. The proposed method has been evaluated experimentally and the results indicate its effectiveness.