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Aesthetic Judgment in Calligraphic Tracing: The Dominant Role of Dynamic Features
Qian Yuan1, Guoying Yang1, Ruimin Lyu1,2
1School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214125, China.
Abstract:
Aesthetic judgment in visual arts has traditionally focused on static features, yet research suggests that dynamic features also shape aesthetic experience. This study examines the dominance of dynamic features in calligraphic tracing aesthetics. Using a custom-designed calligraphy acquisition system, we recorded calligraphy experts and novices imitating Chinese characters and presented their works in three formats: static result sequence video s, pen-holding writing video f, and brushstroke trajectory video b. Participants then rated the stimuli on aesthetic dimensions. Results show that stimuli containing motion cues (f and b) received significantly higher ratings than static stimuli (s), confirming the positive role of dynamic features. Additionally, traced results maintained high structural similarity across writers. And the predictive power of static features for aesthetic scores was limited. This confirms the weak influence of static features on the aesthetics of calligraphic tracing. In conclusion, this study reveals that dynamic features play a dominant role in aesthetic judgment within the context of calligraphic tracing. These findings contribute to aesthetic modeling, proposing that observers dynamically adjust the weighting of static and dynamic features based on aesthetic context to form aesthetic judgments, thereby offering a novel perspective for research on aesthetic cognition mechanisms.
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