Bi-space pyramid match kernel for image object classification

Local features based bi-space pyramid match kernel(BSPM) was proposed for image object classification.In both feature space and image space,a unified multi-resolution framework was built using the local features in order to better describe the semantic content of an image.The pyramids can be built in both the feature space and image space with the proposed method,and the positive definite kernel function can be obtained through suitable matching.This function with linear computation cost can be used in kernel-based learning algorithms.The BSPM was embedded into the support vector machine for image classification on the public image databases,and the experiments show that the proposed method can achieves good classification ability and outperform both vocabulary-guided pyramid match kernel and spatial pyramid match kernel.