Is this done in form of unsupervised (clustering) or suppervised learning?
Unsupervised
With the exponential growth in the usage of social media to share live updates about life, taking pictures has become an unavoidable phenomenon. Individuals unknowingly create a unique knowledge base with these images. The food images, in particular, are of interest as they contain a plethora of information. From the image metadata and using computer vision tools, we can extract distinct insights for each user to build a personal profile. Using the underlying connection between cuisines and their inherent tastes, we attempt to develop such a profile for an individual based solely on the images of his food. Our study provides insights about an individual's inclination towards particular cuisines. Interpreting these insights can lead to the development of a more precise recommendation system. Such a system would avoid the generic approach in favor of a personalized recommendation system.
A picture is worth a thousand words. Complex ideas can easily be depicted via an image. An image is a mine of data in the 21st century. With each person taking an average of 20 photographs every day, the number of photographs taken around the world each year is astounding. According to a Statista report on Photographs, an estimated 1.2 trillion photographs were taken in 2017 and 85% of those images were of food. Youngsters can't resist taking drool-worthy pictures of their food before tucking in. Food and photography have been amalgamated into a creative art form where even the humble home cooked meal must be captured in the perfect lighting and in the right angle before digging in. According to a YouGov poll, half of Americans take pictures of their food. The sophistication of smart-phone cameras allows users to capture high quality images on their hand held device. Paired with the increasing popularity of social media platforms such as Facebook and Instagram, it makes sharing of photographs much easier than with the use of a standalone camera. Thus, each individual knowingly or unknowingly creates a food log. A number of applications such as MyFitnessPal, help keep track of a user's food consumption. These applications are heavily dependent on user input after every meal or snack. They often include several data fields that have to be manually filled by the user. This tedious process discourages most users, resulting in a sparse record of their food intake over time. Eventually, this data is not usable. On the other hand, taking a picture of your meal or snack is an effortless exercise. Food images may not give us an insight into the quantity or quality of food consumed by the individual but it can tell us what he/she prefers to eat or likes to eat. We try to tackle the following research question with our work: Can we predict the cuisine of a food item based on just it's picture, with no additional text input from the user?