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Usability Evaluation of Augmented Reality: A Neuro-Information-Systems Study
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Augmented Reality Based Interactive Cooking Guide.

Isaias Majil1, Mau-Tsuen Yang1, Sophia Yang2

  • 1Department of Computer Science & Information Engineering, National Dong Hwa University, Hualien 974301, Taiwan.

Sensors (Basel, Switzerland)
|November 11, 2022
PubMed
Summary

This study introduces an augmented reality (AR) headset for cooking assistance. The system recognizes ingredients using computer vision (CV) and guides users through recipes with hand gestures, receiving high user satisfaction.

Keywords:
AR cookingMagic Leap Oneaugmented realitysmart kitchen

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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Food Technology

Background:

  • Home cooking is an essential life skill.
  • Existing cooking assistance systems often require complex setups with external sensors.
  • There is a need for intuitive and accessible cooking guidance tools.

Purpose of the Study:

  • To develop and evaluate an all-in-one augmented reality (AR) headset system for cooking assistance.
  • To enable users to identify ingredients and follow recipes using natural interactions.
  • To assess the usability and user satisfaction of the proposed AR cooking system.

Main Methods:

  • An augmented reality (AR) headset equipped with a camera and computer vision (CV) algorithms was developed.
  • The system utilizes YOLOv5 for real-time food ingredient recognition and localization.
  • Users interact with the system via natural hand gestures, and step-by-step video tutorials are displayed through the AR headset.

Main Results:

  • The YOLOv5 model, while having lower accuracy than ResNet and ResNeXt, offers efficient multi-ingredient recognition in a single pass.
  • Twenty participants tested the prototype, with 19 recommending the system.
  • All participants reported overall satisfaction with the AR cooking assistance system.

Conclusions:

  • The proposed AR cooking assistance system offers an intuitive and user-friendly approach to home cooking.
  • The system effectively integrates ingredient recognition, recipe guidance, and gesture-based interaction.
  • The positive user feedback indicates strong potential for adoption and further development of AR in culinary applications.