Author :
Qi Chen ; Gang Wang ; Chew Lim Tan
Author_Institution :
Sch. of Comput., Nat. Univ. of Singapore, Singapore, Singapore
Abstract :
We propose a method to try to model fashionable dresses in this paper. We first discover common visual patterns that appear in dress images using a human-in-the-loop, active clustering approach. A fashionable dress is expected to contain certain visual patterns which make it fashionable. An approach is proposed to jointly identify fashionable visual patterns and learn a discriminative fashion classifier. The results show that interesting fashionable patterns can be discovered on a newly collected dress dataset. Furthermore, our model can also achieve high accuracy on distinguishing fashionable and unfashionable dresses.
Keywords :
clothing; clothing industry; computer vision; image classification; pattern clustering; active clustering; discriminative fashion classifier; dress dataset; dress images; fashion modeling; fashionable dress model; fashionable visual patterns; human-in-the-loop clustering; unfashionable dresses; Clothing; Computational modeling; Image color analysis; Kernel; Support vector machines; Training; Visualization; Active Clustering; Fashion Classification; Visual Patten Discovery;
Conference_Titel :
Multimedia and Expo (ICME), 2013 IEEE International Conference on
Conference_Location :
San Jose, CA
DOI :
10.1109/ICME.2013.6607545