Paper Info
Title
Representative photo selection for restaurants in food blogs
Abstract
Nowadays, people write comments of restaurants and upload related photos to food blogs after visiting there. Developing a mobile application which enables the user to effectively search restaurants from data in these blogs becomes an emerging need. Besides reading the comments, most people will give a glance at food photos of a restaurant and then decide whether to go or what to eat. Therefore, we propose a system to analyze and select representative photos for each restaurant based on blog-platform media. A strong food detection model is trained to retrieve food photos and an aesthetic quality assessment method is utilized to select representative photos. Based on these representative photos, users can more easily have the impression of the restaurant and review the blog in an organized way. The experimental results show that our system can generate better representative photos (i.e. much closer to the users' preferences) than existing blog platforms.
Year
DOI
Venue
2015
10.1109/ICMEW.2015.7169814
2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
Keywords
Field
DocType
Representative Photo Selection,Photo Quality Assessment,Food Detection
Computer science,Multimedia
Conference
ISSN
Citations 
PageRank 
2330-7927
2
0.36
References 
Authors
11
4
Name
Order
Citations
PageRank
Yi-Jyun Chang120.36
Hung-Yi Lo21188.33
Min-Shan Huang320.36
Min-Chun Hu417029.78