Feature representation and learning methods in visual search applications - Manandhar, Dipu (2019)
This thesis studies and develops various image feature representation and learning methods for visual search applications. We study both handcrafted features as well as deep learning based representations. Handcrafted features based methods are light-weight and do not require large training data. However, they have been outperformed by deep learning methods in various vision-related problems in recent years. Nevertheless, deep learning methods generally require large data and computational power. In view of this, this thesis will study both handcrafted methods as well as deep learning methods for two selected domains, namely, visual landmark search and visual fashion search and application.