Unsupervised topic hypergraph hashing for efficient mobile image retrieval

• Main Authors: ZHU, Lei, SHEN, Jialie, XIE, Liang, CHENG, Zhiyong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Codes (symbols); topic hypergraph hashing; Factorization; Semantics; Fast retrievals; High dimensional feature; High-order; Hyperedges; Low-level features; Nonnegative matrix factorization; Semantic relations; State-of-the-art methods; Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/3537; https://ink.library.smu.edu.sg/context/sis_research/article/4538/viewcontent/UnsupervisedTopicHypergraphHashing_2016.pdf
• Institution: Singapore Management University

Hashing compresses high-dimensional features into compact binary codes. It is one of the promising techniques to support efficient mobile image retrieval, due to its low data transmission cost and fast retrieval response. However, most of existing hashing strategies simply rely on low-level features...