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Conveying Semantics through Visual Metaphor
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DOI：10.1145/2589483.png)
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摘要
En 中文
In the field of visual art, metaphor is a way to communicate meaning to the viewer. We present a computational system for communicating visual metaphor that can identify adjectives for describing an image based on a low-level visual feature representation of the image. We show that the system can use this visual-linguistic association to render source images that convey the meaning of adjectives in a way consistent with human understanding. Our conclusions are based on a detailed analysis of how the system's artifacts cluster, how these clusters correspond to the semantic relationships of adjectives as documented in WordNet, and how these clusters correspond to human opinion.
Keyword:
Design
Algorithms
Performance
Visual metaphor
evolutionary art
neural networks
clustering
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期刊
IF:
6.6
论文数:
1.5K
被引数:
6.2K
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