Vision-Based Approaches for Automatic Food Recognition and Dietary Assessment

A Survey

Mohammed Ahmed Subhi, Sawal Hamid Md Ali, Mohammed Abulameer Mohammed

Research output: Contribution to journalArticle

Abstract

Consuming the proper amount and right type of food have been the concern of many dieticians and healthcare conventions. In addition to physical activity and exercises, maintaining a healthy diet is necessary to avoid obesity and other health-related issues, such as diabetes, stroke, and many cardiovascular diseases. Recent advancements in machine learning applications and technologies have made it possible to develop automatic or semi-automatic dietary assessment solutions, which is a more convenient approach to monitor daily food intake and control eating habits. These solutions aim to address the issues found in the traditional dietary monitoring systems that suffer from imprecision, underreporting, time consumption, and low adherence. In this paper, the recent vision-based approaches and techniques have been widely explored to outline the current approaches and methodologies used for automatic dietary assessment, their performances, feasibility, and unaddressed challenges and issues.

Original languageEnglish
Article number8666636
Pages (from-to)35370-35381
Number of pages12
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 1 Jan 2019

Fingerprint

Nutrition
Medical problems
Learning systems
Health
Monitoring

Keywords

  • food classification
  • food image datasets
  • food nutrient information
  • Food recognition
  • food volume estimation

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Cite this

Vision-Based Approaches for Automatic Food Recognition and Dietary Assessment : A Survey. / Subhi, Mohammed Ahmed; Md Ali, Sawal Hamid; Mohammed, Mohammed Abulameer.

In: IEEE Access, Vol. 7, 8666636, 01.01.2019, p. 35370-35381.

Research output: Contribution to journalArticle

Subhi, Mohammed Ahmed ; Md Ali, Sawal Hamid ; Mohammed, Mohammed Abulameer. / Vision-Based Approaches for Automatic Food Recognition and Dietary Assessment : A Survey. In: IEEE Access. 2019 ; Vol. 7. pp. 35370-35381.
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