Scene Identification Using Discriminitive Pattern

Abstract

Scene Identification is the process of retrieving relevant information about an image. This can be used in modern life in various ways. The image clicked by a mobile camera can be input to a remote server which returns some relevant information about the image or what we call as scene. In this project we have worked on a method for scene identification using discriminitive patterns. We rank the image patches sampled from target images. For classification purposes, we have used Support Vector Classifiers. SVMs are trained using top discriminitive patches of image classes. We vary number of top discriminitive patches and finally get the number of discriminitive patterns which yields the best result. For demonstration, we have used NIT Rourkela Building dataset.