Back to articles
Articles
Volume: 33 | Article ID: art00011
Image
An End-to-End Food Image Analysis System
  DOI :  10.2352/ISSN.2470-1173.2021.8.IMAWM-285  Published OnlineJanuary 2021
Abstract

Modern deep learning techniques have enabled advances in image-based dietary assessment such as food recognition and food portion size estimation. Valuable information on the types of foods and the amount consumed are crucial for prevention of many chronic diseases. However, existing methods for automated image-based food analysis are neither end-to-end nor are capable of processing multiple tasks (e.g., recognition and portion estimation) together, making it difficult to apply to real life applications. In this paper, we propose an image-based food analysis framework that integrates food localization, classification and portion size estimation. Our proposed framework is end-to-end, i.e., the input can be an arbitrary food image containing multiple food items and our system can localize each single food item with its corresponding predicted food type and portion size. We also improve the single food portion estimation by consolidating localization results with a food energy distribution map obtained by conditional GAN to generate a four-channel RGB-Distribution image. Our end-to-end framework is evaluated on a real life food image dataset collected from a nutrition feeding study.

Subject Areas :
Views 58
Downloads 15
 articleview.views 58
 articleview.downloads 15
  Cite this article 

Jiangpeng He, Runyu Mao, Zeman Shao, Janine L. Wright, Deborah A. Kerr, Carol J. Boushey, Fengqing Zhu, "An End-to-End Food Image Analysis Systemin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2021,  pp 285-1 - 285-7,  https://doi.org/10.2352/ISSN.2470-1173.2021.8.IMAWM-285

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2021
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
IS&T 7003 Kilworth Lane Springfield, VA 22151 USA