Abstract
Object recognition in scenes is a topic of recent interest due to the technologies and data sets currently available for image and video data. However, in real application data there is often a significant variation within the samples available for each object (class) to be recognized. This issue can hamper the use of regular supervised learning methods. This project aims to study algorit…