Hidayati, Shintami C.Shintami C.HidayatiWEN-HUANG CHENGHua, Kai LungKai LungHua2023-03-132023-03-132012-12-269781450310895https://scholars.lib.ntu.edu.tw/handle/123456789/629228This paper presents a novel approach to automatically classify the upperwear genre from a full-body input image with no restrictions of model poses, image backgrounds, and image resolutions. Five style elements, that are crucial for clothing recognition, are identified based on the clothing design theory. The corresponding features of each of these style elements are also designed. We illustrate the effectiveness of our approach by showing that the proposed algorithm achieved overall precision of 92.04%, recall of 92.45%, and F score of 92.25% with 1,077 clothing images crawled from popular online stores. © 2012 ACM.classification | clothing genre | style elementconference paper10.1145/2393347.23964022-s2.0-84871391698https://api.elsevier.com/content/abstract/scopus_id/84871391698