Image processing methods utilizing motion information

Dissertation

Jun Ma

Research output: ThesisDissertationCollection of Articles

Abstract

This thesis concerns the development of methods and algorithms for image sequence analysis.The study covers a wide range.However, motion as a common feature runs through the whole thesis.The following topics have been covered in the thesis: motion estimation from an image sequence, determination of depth from a zooming image sequence, estimation of 3-D parameters, moving object recognition and image sequence coding.Motion estimation from an image sequence is considered and a 2-D displacement vector field is estimated for various applications.A new motion constraint equation is presented to avoid the problem caused by non-uniform illumination.A new additional constraint is introduced to preserve the discontinuities in the estimation.The estimated 2-D displacement vector field is successfully applied to image segmentation.A zooming camera is considered for determination of surface depth in a static scene.Camera zooming can be regarded as a special type of motion and depth can be recovered from the zooming image sequence.Two schemes are discussed.Image irradiance equations for a zooming camera are developed.The estimation of 3-D parameters from a 2-D image sequence is studied.An algorithm which uses only three straight line correspondences over two frames is presented.Image recognition for moving objects is considered.A fast shape descriptor is presented and a relaxation labeling based edge detector is developed.This fast shape descriptor has some advantages over the Fourier descriptors.The fast shape descriptor is applied to airplane tracking.Two schemes for image compression are investigated.The first-scheme presents a novel idea for image sequence coding and it emphasizes the use of temporal derivatives.The second scheme discusses a fractal based image compression method.The images are split into a group of small squares according to its fractal dimension instead of contour.
Original languageEnglish
QualificationDoctor Degree
Awarding Institution
  • Tampere University of Technology (TUT)
Award date3 Nov 1989
Place of PublicationEspoo
Publisher
Print ISBNs951-38-3561-8
Publication statusPublished - 1989
MoE publication typeG5 Doctoral dissertation (article)

Fingerprint

Image processing
Cameras
Motion estimation
Image compression
Image recognition
Object recognition
Fractal dimension
Image segmentation
Fractals
Labeling
Lighting
Aircraft
Derivatives
Detectors

Keywords

  • image processing
  • picture processing
  • computer vision

Cite this

Ma, J. (1989). Image processing methods utilizing motion information: Dissertation. Espoo: VTT Technical Research Centre of Finland.
Ma, Jun. / Image processing methods utilizing motion information : Dissertation. Espoo : VTT Technical Research Centre of Finland, 1989. 127 p.
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abstract = "This thesis concerns the development of methods and algorithms for image sequence analysis.The study covers a wide range.However, motion as a common feature runs through the whole thesis.The following topics have been covered in the thesis: motion estimation from an image sequence, determination of depth from a zooming image sequence, estimation of 3-D parameters, moving object recognition and image sequence coding.Motion estimation from an image sequence is considered and a 2-D displacement vector field is estimated for various applications.A new motion constraint equation is presented to avoid the problem caused by non-uniform illumination.A new additional constraint is introduced to preserve the discontinuities in the estimation.The estimated 2-D displacement vector field is successfully applied to image segmentation.A zooming camera is considered for determination of surface depth in a static scene.Camera zooming can be regarded as a special type of motion and depth can be recovered from the zooming image sequence.Two schemes are discussed.Image irradiance equations for a zooming camera are developed.The estimation of 3-D parameters from a 2-D image sequence is studied.An algorithm which uses only three straight line correspondences over two frames is presented.Image recognition for moving objects is considered.A fast shape descriptor is presented and a relaxation labeling based edge detector is developed.This fast shape descriptor has some advantages over the Fourier descriptors.The fast shape descriptor is applied to airplane tracking.Two schemes for image compression are investigated.The first-scheme presents a novel idea for image sequence coding and it emphasizes the use of temporal derivatives.The second scheme discusses a fractal based image compression method.The images are split into a group of small squares according to its fractal dimension instead of contour.",
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Ma, J 1989, 'Image processing methods utilizing motion information: Dissertation', Doctor Degree, Tampere University of Technology (TUT), Espoo.

Image processing methods utilizing motion information : Dissertation. / Ma, Jun.

Espoo : VTT Technical Research Centre of Finland, 1989. 127 p.

Research output: ThesisDissertationCollection of Articles

TY - THES

T1 - Image processing methods utilizing motion information

T2 - Dissertation

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N2 - This thesis concerns the development of methods and algorithms for image sequence analysis.The study covers a wide range.However, motion as a common feature runs through the whole thesis.The following topics have been covered in the thesis: motion estimation from an image sequence, determination of depth from a zooming image sequence, estimation of 3-D parameters, moving object recognition and image sequence coding.Motion estimation from an image sequence is considered and a 2-D displacement vector field is estimated for various applications.A new motion constraint equation is presented to avoid the problem caused by non-uniform illumination.A new additional constraint is introduced to preserve the discontinuities in the estimation.The estimated 2-D displacement vector field is successfully applied to image segmentation.A zooming camera is considered for determination of surface depth in a static scene.Camera zooming can be regarded as a special type of motion and depth can be recovered from the zooming image sequence.Two schemes are discussed.Image irradiance equations for a zooming camera are developed.The estimation of 3-D parameters from a 2-D image sequence is studied.An algorithm which uses only three straight line correspondences over two frames is presented.Image recognition for moving objects is considered.A fast shape descriptor is presented and a relaxation labeling based edge detector is developed.This fast shape descriptor has some advantages over the Fourier descriptors.The fast shape descriptor is applied to airplane tracking.Two schemes for image compression are investigated.The first-scheme presents a novel idea for image sequence coding and it emphasizes the use of temporal derivatives.The second scheme discusses a fractal based image compression method.The images are split into a group of small squares according to its fractal dimension instead of contour.

AB - This thesis concerns the development of methods and algorithms for image sequence analysis.The study covers a wide range.However, motion as a common feature runs through the whole thesis.The following topics have been covered in the thesis: motion estimation from an image sequence, determination of depth from a zooming image sequence, estimation of 3-D parameters, moving object recognition and image sequence coding.Motion estimation from an image sequence is considered and a 2-D displacement vector field is estimated for various applications.A new motion constraint equation is presented to avoid the problem caused by non-uniform illumination.A new additional constraint is introduced to preserve the discontinuities in the estimation.The estimated 2-D displacement vector field is successfully applied to image segmentation.A zooming camera is considered for determination of surface depth in a static scene.Camera zooming can be regarded as a special type of motion and depth can be recovered from the zooming image sequence.Two schemes are discussed.Image irradiance equations for a zooming camera are developed.The estimation of 3-D parameters from a 2-D image sequence is studied.An algorithm which uses only three straight line correspondences over two frames is presented.Image recognition for moving objects is considered.A fast shape descriptor is presented and a relaxation labeling based edge detector is developed.This fast shape descriptor has some advantages over the Fourier descriptors.The fast shape descriptor is applied to airplane tracking.Two schemes for image compression are investigated.The first-scheme presents a novel idea for image sequence coding and it emphasizes the use of temporal derivatives.The second scheme discusses a fractal based image compression method.The images are split into a group of small squares according to its fractal dimension instead of contour.

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KW - picture processing

KW - computer vision

M3 - Dissertation

SN - 951-38-3561-8

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Ma J. Image processing methods utilizing motion information: Dissertation. Espoo: VTT Technical Research Centre of Finland, 1989. 127 p.