Can consumers' visual attention be predictable? A saliency modelling-based approach on fashion advertisements. Issue 3 (2nd September 2021)

• Record Type: Journal Article
• Authors: Lee, Seung-Hee; Liang, Yuli; Chen, Ying; Mahdi, Ali; Qin, Jun
• Is Part Of: International journal of fashion design, technology and education. Volume 14:Issue 3(2021)
• Page Start: 253
• Page End: 262
• Publication Date: 2021-09-02
• Subjects: Visual attention -- fashion images -- prediction -- saliency modelling -- fashion advertisements; Fashion design -- Periodicals; Clothing trade -- Periodicals; 746.92
• DOI: 10.1080/17543266.2021.1925354
• Languages: English
• ISSNs: 1754-3266

Abstract

ABSTRACT: As collaborative research between engineering and fashion, the purpose of this study was to investigate if saliency models can be applied for predicting consumers' visual attention to fashion images such as fashion advertisements. A human subject study was conducted to record human visual fixations on 10 colour fashion advertisement images, which were randomly selected from fashion magazines. The participants include 67 college students (26 males and 41 females). All mouse-tracking locations on images were recorded and saved using Psychtoolbox-3 with MATLAB. The locations represent the human fixation points on the images and are used to generate fixation maps. This collaborative research is an innovative and pioneering approach to predict consumers' visual attention toward fashion images using saliency models. From the results of this study, the engineering area's saliency models were proven as effective measurements in predicting fashion consumers' visual attention when looking at fashion images such as advertisements.