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Social Media Image Recognition for Food Trend Analysis

Contributo in Atti di convegno
Data di Pubblicazione:
2017
Abstract:
n increasing number of people share their thoughts and the images of their lives on social media platforms. People are exposed to food in their everyday lives and share on-line what they are eating by means of photos taken to their dishes. The hashtag #foodporn is constantly among the popular hashtags in Twitter and food photos are the second most popular subject in Instagram after selfies. The system that we propose, WorldFoodMap, captures the stream of food photos from social media and, thanks to a CNN food image classifier, identifies the categories of food that people are sharing. By collecting food images from the Twitter stream and associating food category and location to them, WorldFoodMap permits to investigate and interactively visualize the popularity and trends of the shared food all over the world.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
Social media; Image recognition; Trend analysis
Elenco autori:
Muntean, Cristina; MONTEIRO DE LIRA, VINICIUS CEZAR; Amato, Giuseppe; Renso, Chiara; Bolettieri, Paolo; Perego, Raffaele
Autori di Ateneo:
AMATO GIUSEPPE
BOLETTIERI PAOLO
MUNTEAN CRISTINA-IOANA
PEREGO RAFFAELE
RENSO CHIARA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/333407
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URL

https://dl.acm.org/citation.cfm?id=3084142
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