Real-time mobile recipe recommendation system using food ingredient recognition

Authors:
Takuma Maruyama;Yoshiyuki Kawano;Keiji Yanai
Affiliations:
The University of Electro-Communications, Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan
Venue:
Proceedings of the 2nd ACM international workshop on Interactive multimedia on mobile and portable devices
Year:
2012

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Abstract

In this paper, we propose a mobile cooking recipe recom mendation system employing object recognition for food ingredients such as vegetables and meats. The proposed system carries out object recognition on food ingredients in a real-time way on an Android-based smartphone, and recommends cooking recipes related to the recognized food ingredients. By only pointing a built-in camera on a mobile device to food ingredients, the user can obtain a recipe list instantly. As an object recognition method, we adopt bag-of-features with SURF and color histogram extracted from multiple images as image features and linear SVM with the one-vs-rest strategy as a classifier. We built 30 kinds of food ingredient short video database for experiments. With this database, we achieved the 83.93% recognition rate within the top six candidates. In the experiment, we made user study by comparing mobile recipe recommendation systems with/without ingredient recognition.