Additive Nearest Neighbor Feature Maps

作者：Wang Zhenzhen^*; Yuan Xiao Tong; Liu Qingshan; Yan Shuicheng

来源：IEEE International Conference on Computer Vision, 2015-12-11 To 2015-12-18.

DOI：10.1109/ICCV.2015.328

In this paper, we present a concise framework to approximately construct feature maps for nonlinear additive kernels such as the Intersection, Hellinger's, and chi(2) kernels. The core idea is to construct a set of anchor points for each individual feature and assign to every query the feature map of its nearest neighbor or the weighted combination of those of its k-nearest neighbors in the anchors. The constructed feature maps can be compactly stored by a group of nearest neighbor (binary) indication vectors along with the anchor feature maps. The approximation error of such an anchored feature mapping approach is analyzed. We evaluate the performance of our approach on large-scale nonlinear support vector machines (SVMs) learning tasks in the context of visual object classification. Experimental results on several benchmark data sets show the superiority of our method over existing feature mapping methods in achieving reasonable tradeoff between training time and testing accuracy.

• 出版日期2015
• 单位南京信息工程大学