Evaluation Metrics for Automated Typographic Poster Generation
CoRR(2024)
摘要
Computational Design approaches facilitate the generation of typographic
design, but evaluating these designs remains a challenging task. In this paper,
we propose a set of heuristic metrics for typographic design evaluation,
focusing on their legibility, which assesses the text visibility, aesthetics,
which evaluates the visual quality of the design, and semantic features, which
estimate how effectively the design conveys the content semantics. We
experiment with a constrained evolutionary approach for generating typographic
posters, incorporating the proposed evaluation metrics with varied setups, and
treating the legibility metrics as constraints. We also integrate emotion
recognition to identify text semantics automatically and analyse the
performance of the approach and the visual characteristics outputs.
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