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Αbstract

Abstract

The current thesis has been written as part of the undergraduate studies for the

department of Electrical and Computer Engineering of Patras University. Its objective

is the three-dimensional (3D) reconstruction from two, at least, photographs, which is

part of computer vision. More specifically, this thesis analyzes in detail the case of

stereo vision when the camera, among two successive shots of the same image, has

zero relative rotation compared to its initial position and an average translation of

about 5 cm. In this way, it attempts to simulate human vision since this is essential for

many Artificial Intelligence applications.

Humans take stereo vision for granted since they live in a three-dimensional

world. However, this world becomes two-dimensional when recorded by a camera.

We can still get information about the image depth but this is empirically done based

on comparing various heights, shapes and sizes. Images are identified by the

computer as any other file. Computers cannot draw conclusions about what is

depicted in the real world. They need to combine at least two images of the same

scene and of different positions to identify the image’s depth.

This process is described in the current thesis. The first chapter describes

stereo vision and why it is so useful. The second chapter provides the basic principles

of projective geometry, the mathematical background for passing from the twodimensional

level to the three-dimensional. The third chapter refers to camera

modeling and its parameters ( instrisic and extrinsic). Chapter four analyzes the

camera calibration process. Chapter five explains the matching process of points of

interest in both pictures. The sixth chapter provides the basic principles of epipolar

geometry. The seventh chapter shows the experimental procedure that we followed in

order to estimate the depth of the scene. Chapter eight shows how the 3D

reconstruction is finally done. Chapter nine talks about our conclusions and how the

results could improve.

Both theoretical and experimental parts of this project cover the key points of

3d reconstruction. The results of the experiments show that the existing methods are

satisfying but could improve more.

We want to thank our supervisor professor Mr. Dermatas for his collaboration

and his understanding.

ii

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