TY - GEN
T1 - Clothing genre classification by exploiting the style elements
AU - Hidayati, Shintami C.
AU - Cheng, Wen Huang
AU - Hua, Kai Lung
PY - 2012
Y1 - 2012
N2 - This 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.
AB - This 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.
KW - classification
KW - clothing genre
KW - style element
UR - http://www.scopus.com/inward/record.url?scp=84871391698&partnerID=8YFLogxK
U2 - 10.1145/2393347.2396402
DO - 10.1145/2393347.2396402
M3 - Conference contribution
AN - SCOPUS:84871391698
SN - 9781450310895
T3 - MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
SP - 1137
EP - 1140
BT - MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
T2 - 20th ACM International Conference on Multimedia, MM 2012
Y2 - 29 October 2012 through 2 November 2012
ER -