Feature extraction for fashion trend detection - ABDELRAHMAN, SALMA (The Graduate School, Ajou University, 2015)
Abstract This research work is aimed to digitally study and analyze fashion and cloths’ design by mining fashion images. The ultimate goal would be detecting fashion trends and find design and fashion patterns that will help in predicting fashion and the general public reaction and the level of success or failure certain designs and collections may face. The process to reach that goal involves studying existing algorithms and approaches for image processing and computer vision, as in texture analysis, image enhancement and color theory. And studying existing work on fashion analysis and fashion recommendation engines that serves E-commerce and online shopping sites, which developed algorithms for computer vision and feature extraction which specifically targets cloth and fashion images. And finally, work with the accumulative knowledge on fashion and cloths image analysis to develop and propose my own feature set that I think can reflect and represent deigns, and help transfer the visual content to an abstract data sets, that we can apply upon it different machine learning and data mining techniques to reach our original set of goals. So the main challenge in this research is to reach the best set of features that can be extracted from a huge set images, fashion runway images, which are take in different times, conditions and using different technologies with different backgrounds and resolutions.
학위논문(석사)--아주대학교 일반대학원 :컴퓨터공학과,2015. 8
Keywords: computer vision; data mining; image mining; image recognition; feature extraction