Online multimodal co-indexing and retrieval of weakly labeled web image collections

• Main Authors: MENG, Lei, TAN, Ah-hwee, LEUNG, Cyril, NIE, Liqiang, CHUA, Tan-Seng, MIAO, Chunyan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Hierarchical image co-indexing; multimodal search; online learning; clustering; weakly supervised learning; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/5473; https://ink.library.smu.edu.sg/context/sis_research/article/6476/viewcontent/OnlineMultimodalCo_indexingandRetrievalofWeaklyLabeledWebImageCollections.pdf
• Institution: Singapore Management University

Weak supervisory information of web images, such as captions, tags, and descriptions, make it possible to better understand images at the semantic level. In this paper, we propose a novel online multimodal co-indexing algorithm based on Adaptive Resonance Theory, named OMC-ART, for the automatic co-...