Real-time Mobile Recipe Recommendation System Using Food Ingredient Recognition

In this paper, we propose a mobile cooking recipe recom-mendation system employing object recognition for food in-gredients such as vegetables and meats. The proposed sys-tem carries out object recognition on food ingredients in a real-time way on an Android-based smartphone, and rec-ommends cooking recipes related to the recognized food in-gredients. 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 classier. 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