Feature selection in multimedia: The state-of-the-art review

Multimedia data mining, particularly feature selection (FS), has been successfully applied in recent classification and recognition works. However, only a few studies in the contemporary literature have reviewed FS (e.g., analyses of data pre-processing prior to classification and clustering). This study aimed to fill this research gap by presenting an extensive survey on the current development of FS in multimedia. A total of 70 related papers published from 2001 to 2017 were collected from multiple databases. Breakdowns and analyses were performed on data types, methods, search strategies, performance measures, and challenges. The development trend of FS presages the increased prominence of heuristic search strategies and hybrid FS in the latest multimedia data mining.