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Analyzing color harmony of food images

Conference Paper
Publication Date:
2019
abstract:
Color of food images play a key role in human perception of food quality and calories, as well as in food choice. In this paper we investigate the use of computational methods for color harmony analysis of food images. To this end we propose a computational pipeline that includes color segmentation, color palette extraction and color harmony prediction. Such a pipeline makes it possible to analyze the emotions elicited by pairs and multiple combinations of food dishes.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
color; color segmentation; computational pipeline; color harmony prediction; machine learning; deep learning; color palette extraction
List of contributors:
Gagliardi, Isabella; Artese, MARIA TERESA
Authors of the University:
ARTESE MARIA TERESA
GAGLIARDI ISABELLA
Handle:
https://iris.cnr.it/handle/20.500.14243/382203
Book title:
27th Color and Imaging Conference Final Program and Proceedings
Published in:
FINAL PROGRAM AND PROCEEDINGS - IS&T/SID COLOR IMAGING CONFERENCE
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URL

https://www.ingentaconnect.com/content/ist/cic/2019/00002019/00000001/art00066;jsessionid=1nokew058n3i8.x-ic-live-03
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