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Band 5

Artificial Neural Networks for Computer Vision

Aus der Reihe Research Notes in Neural Computing

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.12.1991

Verlag

Springer Us

Seitenzahl

170

Maße (L/B/H)

23,5/15,5/1,1 cm

Gewicht

289 g

Auflage

1992

Sprache

Englisch

ISBN

978-0-387-97683-9

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.12.1991

Verlag

Springer Us

Seitenzahl

170

Maße (L/B/H)

23,5/15,5/1,1 cm

Gewicht

289 g

Auflage

1992

Sprache

Englisch

ISBN

978-0-387-97683-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Artificial Neural Networks for Computer Vision
  • Produktbild: Artificial Neural Networks for Computer Vision
  • 1 Introduction.- 1.1 Neural Methods.- 1.2 Plan of the Book.- 2 Computational Neural Networks.- 2.1 Introduction.- 2.2 Amari and Hopfield Networks.- 2.3 A Discrete Neural Network for Vision.- 2.3.1 A Discrete Network.- 2.3.2 Decision Rules.- 2.4 Discussion.- 3 Static Stereo.- 3.1 Introduction.- 3.2 Depth from Two Views.- 3.3 Estimation of Intensity Derivatives.- 3.3.1 Fitting Data Using Chebyshev Polynomials.- 3.3.2 Analysis of Filter M(y).- 3.3.3 Computational Consideration for the Natural Images.- 3.4 Matching Using a Network.- 3.5 Experimental Results.- 3.5.1 Random Dot Stereograms.- 3.5.2 Natural Stereo Images.- 3.6 Discussion.- 4 Motion Stereo—Lateral Motion.- 4.1 Introduction.- 4.2 Depth from Lateral Motion.- 4.3 Estimation of Measurement Primitives.- 4.3.1 Estimation of Derivatives.- 4.3.2 Estimation of Chamfer Distance Values.- 4.4 Batch Approach.- 4.4.1 Estimation of Pixel Positions.- 4.4.2 Batch Formulation.- 4.5 Recursive Approach.- 4.6 Matching Error.- 4.7 Detection of Occluding Pixels.- 4.8 Experimental Results.- 4.9 Discussion.- 5 Motion Stereo—Longitudinal Motion.- 5.1 Introduction.- 5.2 Depth from Forward Motion.- 5.2.1 General Case: Images Are Nonequally Spaced.- 5.2.2 Special Case: Images Are Equally Spaced.- 5.3 Estimation of the Gabor Features.- 5.3.1 Gabor Correlation Operator.- 5.3.2 Computational Considerations.- 5.4 Neural Network Formulation.- 5.5 Experimental Results.- 5.6 Discussion.- 6 Computation of Optical Flow.- 6.1 Introduction.- 6.2 Estimation of Intensity Values and Principal Curvatures.- 6.2.1 Estimation of Polynomial Coefficients.- 6.2.2 Computing Principal Curvatures.- 6.2.3 Analysis of Filters.- 6.3 Neural Network Formulation.- 6.3.1 Physiological Considerations.- 6.3.2 Computational Considerations.- 6.3.3 Computing Flow Field.- 6.4 Detection of Motion Discontinuities.- 6.5 Multiple Frame Approaches.- 6.5.1 Batch Approach.- 6.5.2 Recursive Algorithm.- 6.5.3 Detection Rules.- 6.6 Experimental Results.- 6.6.1 Synthetic Image Sequence.- 6.6.2 Natural Image Sequence.- 6.7 Discussion.- 7 Image Restoration.- 7.1 Introduction.- 7.2 An Image Degradation Model.- 7.3 Image Representation.- 7.4 Estimation of Model Parameters.- 7.5 Restoration.- 7.6 A Practical Algorithm.- 7.7 Computer Simulations.- 7.8 Choosing Boundary Values.- 7.9 Comparisons to Other Restoration Methods.- 7.9.1 Inverse Filter and SVD Pseudoinverse Filter.- 7.9.2 MMSE and Modified MMSE Filters.- 7.10 Optical Implementation.- 7.11 Discussion.- 8 Conclusions and Future Research.- 8.1 Conclusions.- 8.2 Future Research.