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Master Thesis: Real Time Enhancement of Nutrition Data for Groceries with Mixed Reality
You will use computer vision to identify food products and build a Unity application for Hololens or Magic Leap one in which users will become able to see the health impact of ingredient data. The app will then help the user to make the healthiest choice amongst the given alternatives.
**The Topic**
It is estimated that in the year 2030 our daily consumption surpasses 3’000 kcal per day. The consequences are dramatic: Obesity, diabetes type II and other overweight related illnesses take a significant toll on patients and the health care
sector. Our project “BetterChoiceAR” will be a digital, Augmented Reality shopping coach and aims to increase transparency between retailers, food producers and consumers: Consumers can stand in front of a product, the headset (Microsoft Hololens or Magic Leap One) can identify products from their package (computer vision with our image database) and visualize relevant information about each product’s ingredients. Your prototype will make grocery decisions easier for consumers, and you should be able to show its feasibility in i) a supermarket scenario and/or ii) a vending machine scenario and/or iii) a kitchen scenario. We want to observe how the AR solution ranks when compared to a product scanning app in terms of consumer attitudes, intention & actual behavior.
**The Thesis**
You build a Unity application in which users will become able to view packaged product items (ingredient data retrieved from our own database). The app will then help the user to make the healthiest choice amongst the products in the field of view. As this entirely digital intervention is a novelty in the retail sector, you have the chance to become a co-author of a
scientific paper in a top conference or journal.
**You are**
You are
• familiar with developing a Unity AR app
• product image & ingredient DB available for quickstart
• experienced with API frameworks
• interested to build the “FitBit” for nutritional health
• capable of reading scientific articles
• motivated to participate on current research
**The Topic** It is estimated that in the year 2030 our daily consumption surpasses 3’000 kcal per day. The consequences are dramatic: Obesity, diabetes type II and other overweight related illnesses take a significant toll on patients and the health care sector. Our project “BetterChoiceAR” will be a digital, Augmented Reality shopping coach and aims to increase transparency between retailers, food producers and consumers: Consumers can stand in front of a product, the headset (Microsoft Hololens or Magic Leap One) can identify products from their package (computer vision with our image database) and visualize relevant information about each product’s ingredients. Your prototype will make grocery decisions easier for consumers, and you should be able to show its feasibility in i) a supermarket scenario and/or ii) a vending machine scenario and/or iii) a kitchen scenario. We want to observe how the AR solution ranks when compared to a product scanning app in terms of consumer attitudes, intention & actual behavior.
**The Thesis** You build a Unity application in which users will become able to view packaged product items (ingredient data retrieved from our own database). The app will then help the user to make the healthiest choice amongst the products in the field of view. As this entirely digital intervention is a novelty in the retail sector, you have the chance to become a co-author of a scientific paper in a top conference or journal.
**You are**
You are • familiar with developing a Unity AR app • product image & ingredient DB available for quickstart • experienced with API frameworks • interested to build the “FitBit” for nutritional health • capable of reading scientific articles • motivated to participate on current research
Your prototype will make grocery decisions easier for consumers, and you should be able to show its feasibility in i) a supermarket scenario and/or ii) a vending machine scenario and/or iii) a kitchen scenario.
Your prototype will make grocery decisions easier for consumers, and you should be able to show its feasibility in i) a supermarket scenario and/or ii) a vending machine scenario and/or iii) a kitchen scenario.
Klaus Fuchs
ETH Zürich, D-MTEC
Weinbergstrasse 56/58
8092 Zürich
Phone: +41 44 633 89 15
fuchsk@ethz.ch
www.autoidlabs.ch
www.im.ethz.ch
Klaus Fuchs ETH Zürich, D-MTEC Weinbergstrasse 56/58 8092 Zürich