Image Retrieval by Cross-Media Relevance Fusion

How to estimate cross-media relevance between a given query and an unlabeled image is a key question in the MSR-Bing Image Retrieval Challenge. We answer the question by proposing cross-media relevance fusion, a conceptually simple framework that exploits the power of individual methods for crossmedia relevance estimation. Four base cross-media relevance functions are investigated, and later combined by weights optimized on the development set. With DCG25 of 0.5200 on the test dataset, the proposed image retrieval system secures the first place in the evaluation. Categories and Subject Descriptors H.3.3 [INFORMATION STORAGE AND RETRIEVAL]: Information Search and Retrieval Keywords Image retrieval challenge, Cross-media relevance fusion

• Type: Journal
• Year: 2015
• Where: MM
• Authors: Jianfeng Dong, Xirong Li, Shuai Liao, Jieping Xu, Duanqing Xu, Xiaoyong Du
• Keywords: MM 2015, Multimedia