Image semantics classification method based on class-shared multiple kernel learning (MKL)

Abstract

An image semantics classification method based on class-shared multiple kernel learning (MKL), which relates to the artificial intelligence field, is disclosed. The method is characterized by: a pretreatment stage: extracting a bottom layer characteristic of an image and calculating a multiple kernel matrix; a modeling stage: constructing a class-shared multiple kernel classifier model; a parameter learning stage: optimizing classifier parameters of multiple classes, basic kernel function weights and kernel function weights which are related to the classes in an uniform frame; an image classification stage: using the classifier with a good learning ability to carry out image classification to a sample to be classified. In the invention, on one hand, through sharing a group of basic kernelfunction weights, common implicit knowledge of each class in a kernel function space can be excavated; on the other hand, characteristics of the each class in the kernel function space can be considered for the different classes which possess class-related kernel function weights. According to a degree of training data, a kernel classification method is provided for the kernel function combination to achieve mutual independence, partial sharing or complete sharing in the classes.

Description

technical field [0001] The invention relates to an image classification and object recognition method, in particular to an image semantic classification method based on class-sharing multi-core learning, which belongs to the field of artificial intelligence, and specifically belongs to the technical field of image understanding. Background technique [0002] With the rapid development of Internet technology and information collection technology, digital information resources are showing an explosive growth trend. In the face of massive image data, people expect to search for the information they need accurately and quickly, but the currently widely used text-based image search technology is not suitable for a large amount of image data without labels and text information. Therefore, automatic machine recognition of image semantic information has become the most urgent demand in the field of multimedia analysis and retrieval. The background technology of the present inventio...

AI Technical Summary

Problems solved by technology

[0011] The technical problem to be solved by the present invention is: in the face of the image semantic classification problem of multiple categories, how to mine the commonality of multiple categories in the multi-kernel function space while learning the individuality of image categories in the multi-kernel function space, so as to make full use of all training samples Contribute to the recognition of image categories, weaken the adverse effects of insufficient training samples, and improve classification accuracy

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