A novel digital image classification algorithm via low-rank sparse bag-of-features model

• Main Authors: ZOU, Xiu-Ming, SUN, Huai-Jiang, YANG, Sai, ZHU, Yan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Bag-of-features; Digital image classification; Low-rank and sparse matrix decomposition; Multiple kernel learning; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research_all/13; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1032&context=sis_research_all
• Institution: Singapore Management University

Bag-of-features (BoF) is one of the most well-known methods used to represent digital image features because of its simplicity and efficiency. A variety of improved algorithms have been employed to enhance the performance of BoF in characterization. However, challenges in the application of BoF in t...