Using Color for Object Recognition

Object Recognition is an important task in many Computer Vision problems. The problem is usually defined as classifying new images given a set of training images. One of the most challenging problems is Category-level Object Recognition which has got attention in the past decade. In this project the work on Fine-grained Category Object Recognition is presented. Despite General Object Recognition, images in this problem have a lot in common. But they still have differences that we can use for the classification. In this research, we use color feature for classification in many different ways. We are going to try to use color features which has not given much attention by the computer vision community to see if we can use it to improve the classification of 200 bird species (CUB200)[7]. The goal is to improve the performance of existing papers [5] [4] and also find more general way to use color in other similar problems.