Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements
This work addresses the need for automated font analytics in design and marketing, though it is incremental as it applies existing techniques to a new dataset.
The paper tackled the problem of understanding font usage in graphic designs by conducting a large-scale statistical study on book covers and online advertisements, revealing trends in how font styles relate to content genres.
In this paper, we conduct a large-scale study of font statistics in book covers and online advertisements. Through the statistical study, we try to understand how graphic designers relate fonts and content genres and identify the relationship between font styles, colors, and genres. We propose an automatic approach to extract font information from graphic designs by applying a sequence of character detection, style classification, and clustering techniques to the graphic designs. The extracted font information is accumulated together with genre information, such as romance or business, for further trend analysis. Through our unique empirical study, we show that the collected font statistics reveal interesting trends in terms of how typographic design represents the impression and the atmosphere of the content genres.