Host: Japan Society of Kansei Engineering
Name : The 5th International Symposium on Affective Science and Engineering
Number : 5
Location : Kogakuin University
Date : March 17, 2019 - March 18, 2019
In this paper, we propose an effective classification method for the silhouettes of various kinds of clothes. There are two approaches to analyzing clothes. The first method focuses on the basic elements of a garment’s design, from the viewpoint of its creator. The second method features detailed categories with respect to the garment made. The silhouette of a garment is one of the most important pieces of information in fashion design trends. Here, we focused on classifying silhouettes that lead to the creation of trends, rather than classifying items made of clothing. This classification makes it possible to create a data set of silhouettes that can be used to multi-class classifications in a deep neural network.
