基于子空间关系学习的跨模态哈希检索方法  

A CROSS MODAL HASH RETRIEVAL METHOD BASED ON SUBSPACE RELATION LEARNING

作　　者：赵永晖 胡海根[2] Zhao Yonghui;Hu Haigen(Zhejiang Guangsha Vocational and Technical University of Construction,Dongyang 322100,Zhejiang,China;College of Computer Science&Technology,Zhejiang University of Technology,Hangzhou 310024,Zhejiang,China)

机构地区：[1]浙江广厦建设职业技术大学,浙江东阳322100 [2]浙江工业大学计算机科学与技术学院,浙江杭州310024

出　　处：《计算机应用与软件》2024年第10期304-313,共10页Computer Applications and Software

基　　金：浙江省自然科学基金项目(LY18F030025)。

摘　　要：为了提升检索精度,降低计算成本,提出一种基于子空间关系学习的跨模态哈希检索方法。通过优化哈希码与关系信息之间的距离,将类标签转换为子空间的关系信息,从而保留了模态关系、离散约束和非线性结构。设计一个对称的框架来生成统一的二进制码检索数据库,并提出一种离散优化散列算法来解决目标函数不放松离散约束,有效地提高训练效率。两个跨模态检索实验结果证明了该方法检索精度较高,计算时间较少。In order to improve the retrieval accuracy and reduce the computational cost,a cross modal hash retrieval method based on subspace relation learning is proposed.By optimizing the distance between the hash code and the relation information,the class label was transformed into the relation information of the subspace,thus preserving the modal relation,discrete constraint and nonlinear structure.A symmetric framework was designed to generate a unified binary code retrieval database,and a discrete optimization Hash algorithm was proposed to solve the problem that the objective function did not relax the discrete constraints,which effectively improved the training efficiency.Two cross modal retrieval experiments show that the proposed method has higher retrieval accuracy and less computation time.

关 键 词：跨模态 哈希算法 检索 二进制码 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]