Studies in Robotic Vision, Optical Illusions and Nonlinear Diffusion Filtering
(2003) In Doctoral Theses in Mathematical Sciences 2003:6.- Abstract
- This thesis is divided into three parts, which all deal with computational analysis and processing of images. However, the settings are quite diverse.They range from robotic camera sensors, over human perception, to physical measurement setups. In spite of this diversity, common theoretical ideas and computational aspects are applied which ties the three different parts closer together.
The first part of the thesis deals with calibration methods for robotic vision. Both the estimation of the intrinsic parameters of the applied camera model, intrinsic camera calibration, and the estimation of the orientation and position of the camera in relation to the end-effector of the robot, hand-eye calibration, are discussed. Two... (More) - This thesis is divided into three parts, which all deal with computational analysis and processing of images. However, the settings are quite diverse.They range from robotic camera sensors, over human perception, to physical measurement setups. In spite of this diversity, common theoretical ideas and computational aspects are applied which ties the three different parts closer together.
The first part of the thesis deals with calibration methods for robotic vision. Both the estimation of the intrinsic parameters of the applied camera model, intrinsic camera calibration, and the estimation of the orientation and position of the camera in relation to the end-effector of the robot, hand-eye calibration, are discussed. Two different methods are presented. The first one explores the constraints that arise when calibrating a single camera or a stereo head configuration using a planar calibration object, while performing translational or general motions. The other one uses estimations of the spatial and temporal intensity derivatives in an image sequence for direct computation of the unknown parameters.
The second part of the thesis discusses a new framework for explaining a number of geometrical optical illusions. It is proposed that noise, that enters into the visual process at different stages, causes the estimation of different features in the observed image to be biased. Different types of error models are discussed and illusions that are best explained by each particular model are presented. The discussion is not restricted to the human visual system and highlights the importance of analyzing the influence of noise and uncertainty in any visual process.
The third and final part of the thesis propose the use of nonlinear diffusion filtering to process images obtained by planar laser-induced fluorescence (PLIF) spectroscopy. In particular, the images in the present application are PLIF images of turbulent flames in combustion processes. Solving a nonlinear diffusion equation using an image of this type as initial value, makes succeeding extraction of interesting quantities, such as the length of the flame boundary, an easy task. An analysis of the properties of nonlinear diffusion filtering in general, and for the present application in particular, is given. (Less) - Abstract (Swedish)
- Popular Abstract in Swedish
Den här avhandlingen behandlar analys och bearbetning av bilder ur ett beräkningsmässigt perspektiv. Den är uppdelad i tre delar, vilka diskuterar bilder i så olika sammanhang som i ett artificiellt seende system för robotar, i det mänskliga seendet och i ett bildbehandlingssystem för analys av förbränningsförlopp i tex bilmotorer.
Den första delen handlar om två stycken nya kalibreringsmetoder för robotseende. För att man ska kunna använda kameror som ögon till en robot måste man estimera vissa parametrar i systemet, som tex fokallängden hos kameran. Efter denna kalibrering kan roboten använda kamerorna för att tex navigera i en okänd miljö.
Den andra delen... (More) - Popular Abstract in Swedish
Den här avhandlingen behandlar analys och bearbetning av bilder ur ett beräkningsmässigt perspektiv. Den är uppdelad i tre delar, vilka diskuterar bilder i så olika sammanhang som i ett artificiellt seende system för robotar, i det mänskliga seendet och i ett bildbehandlingssystem för analys av förbränningsförlopp i tex bilmotorer.
Den första delen handlar om två stycken nya kalibreringsmetoder för robotseende. För att man ska kunna använda kameror som ögon till en robot måste man estimera vissa parametrar i systemet, som tex fokallängden hos kameran. Efter denna kalibrering kan roboten använda kamerorna för att tex navigera i en okänd miljö.
Den andra delen av avhandlingen, som förmodligen är den mest spännande ur ett populärvetenskapligt perspektiv, handlar om geometriska optiska illusioner. Med detta menas geometriska figurer där vi tex uppfattar raka linjer som krökta eller ser en falsk relativ rörelse mellan objekt i en figur. Vi lägger fram en ny beräkningsmässig teori som ger en gemensam förklaring till en stor mängd av sådana illusioner. Illustrationer av ett antal illusioner ges i denna del av avhandlingen, tillsammans med deras förklaringar.
Den tredje delen handlar om att använda olinjära differentialekvationer inom bildbehandling. Speciellt diskuteras användandet av olinjära diffusionsekvationer för att behandla bilder av turbulenta flammor i förbränningsförlopp. Bilderna är framtagna mha så kallad laser-inducerad fluorescens. För dessa typer av bilder visar sig behandling med "diffusionsfiltrering" ge nya bilder som lämpar sig väl för fortsatt analys av de fysikaliska processerna i förbränningsförloppet. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/21322
- author
- Malm, Henrik LU
- supervisor
- opponent
-
- Ph D, D Sc Zhang, Zhengyou, Microsoft Research, USA
- organization
- publishing date
- 2003
- type
- Thesis
- publication status
- published
- subject
- keywords
- hand-eye calibration, camera calibration, nonlinear diffusion filtering, robotic vision, optical illusions, Mathematics, Matematik
- in
- Doctoral Theses in Mathematical Sciences
- volume
- 2003:6
- pages
- 138 pages
- publisher
- Centre for Mathematical Sciences, Lund University
- defense location
- Room MH:B at the Centre for Mathematical Sciences, Lund Institute of Technology
- defense date
- 2003-09-12 10:15:00
- ISSN
- 1404-0034
- ISBN
- 91-628-5778-9
- language
- English
- LU publication?
- yes
- id
- 69950aba-812e-4ff1-b542-d80c2ed416bb (old id 21322)
- date added to LUP
- 2016-04-01 17:04:55
- date last changed
- 2019-05-21 13:31:51
@phdthesis{69950aba-812e-4ff1-b542-d80c2ed416bb,
abstract = {{This thesis is divided into three parts, which all deal with computational analysis and processing of images. However, the settings are quite diverse.They range from robotic camera sensors, over human perception, to physical measurement setups. In spite of this diversity, common theoretical ideas and computational aspects are applied which ties the three different parts closer together.<br/><br>
<br/><br>
The first part of the thesis deals with calibration methods for robotic vision. Both the estimation of the intrinsic parameters of the applied camera model, intrinsic camera calibration, and the estimation of the orientation and position of the camera in relation to the end-effector of the robot, hand-eye calibration, are discussed. Two different methods are presented. The first one explores the constraints that arise when calibrating a single camera or a stereo head configuration using a planar calibration object, while performing translational or general motions. The other one uses estimations of the spatial and temporal intensity derivatives in an image sequence for direct computation of the unknown parameters.<br/><br>
<br/><br>
The second part of the thesis discusses a new framework for explaining a number of geometrical optical illusions. It is proposed that noise, that enters into the visual process at different stages, causes the estimation of different features in the observed image to be biased. Different types of error models are discussed and illusions that are best explained by each particular model are presented. The discussion is not restricted to the human visual system and highlights the importance of analyzing the influence of noise and uncertainty in any visual process.<br/><br>
<br/><br>
The third and final part of the thesis propose the use of nonlinear diffusion filtering to process images obtained by planar laser-induced fluorescence (PLIF) spectroscopy. In particular, the images in the present application are PLIF images of turbulent flames in combustion processes. Solving a nonlinear diffusion equation using an image of this type as initial value, makes succeeding extraction of interesting quantities, such as the length of the flame boundary, an easy task. An analysis of the properties of nonlinear diffusion filtering in general, and for the present application in particular, is given.}},
author = {{Malm, Henrik}},
isbn = {{91-628-5778-9}},
issn = {{1404-0034}},
keywords = {{hand-eye calibration; camera calibration; nonlinear diffusion filtering; robotic vision; optical illusions; Mathematics; Matematik}},
language = {{eng}},
publisher = {{Centre for Mathematical Sciences, Lund University}},
school = {{Lund University}},
series = {{Doctoral Theses in Mathematical Sciences}},
title = {{Studies in Robotic Vision, Optical Illusions and Nonlinear Diffusion Filtering}},
volume = {{2003:6}},
year = {{2003}},
}