A graph model for scene based image analysis and classification using Epipolar Geometry

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2005-05

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Abstract

This thesis presents a system that analyzes a collection of images and generates a model which describes the relationship between them. The main focus is to develop a system which can provide answers to the following two questions: Do the images match? Are they part of the same scene ? The answers to these questions can be used to classify the image collection into distinct groups. This transformation is achieved in three stages of processing. The firstis concerned with detection and extraction of features from images. The second stage focuses on matching the extracted features and the determination of the epipolar geometry. The final stage involves using the results obtained from the previous stage to develop a graph model. The main aim is to efficiently capture and represent the relationship between the images using this model and provide answers to the questions described above in a simple and effective manner. The goal is to classify the image collection into distinct group based on scene analysis by using the answers provided by the model regarding the nature of the relationship between the various images that are part of the given collection.

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Keywords

Image classification, Epipolar geometry, Computer vision

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