AN INTELLIGENT CLOTHES SEARCH SYSTEM BASED ON FASHION STYLES
This work presents an intelligent clothes search system based on domain knowledge, targeted at creating a virtual assistant to search clothes matched to fashion and users expectation using all what have already been in real closet. All what garment essentials and fashion knowledge are from visual images. Users can simply submit the desired image keywords, such as elegant, sporty, casual, and so on, and occasion type, such as formal meeting, outdoor dating, and so on, to the system. And then the fashion style recognition module is activated to search the desired clothes within the personal garment database. Category learning with supervised neural networking is applied to cluster garments into different impression groups. The input stimuli of the neural network are three sensations, warmness, loudness, and softness, which are transformed from the physical garment essentials like major color tone, print type, and fabric material. The system aims to provide such an intelligent user-centric services system functions as a personal fashion advisor.
Intelligent system Knowledge acquisition Cognition Neural network Category learning
CHING-I CHENG DAMON SHING-MIN LIU
Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-yi Department of General Education, Aletheia University, Matou Campus, Tainan county 712, Taiwan
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
1592-1597
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）