Structure from Motion in the Geosciences
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portes grátis
Structure from Motion in the Geosciences
Smith, Mark W.; Quincey, Duncan J.; Carrivick, Jonathan L.
John Wiley & Sons Inc
08/2016
208
Dura
Inglês
9781118895849
15 a 20 dias
Structure from Motion with Multi View Stereo provides hyperscale landform models using images acquired from standard compact cameras and a network of ground control points.
Abbreviations About the companion website Chapter 1: Introduction to Structure from Motion for the geosciences 1.1. The geosciences and related disciplines 1.2. Aim and scope of this book 1.3. The time and the place 1.4. What is Structure from Motion? 1.5. Structure of this book References Chapter 2: The place of Structure from Motion: a new paradigm in topographic surveying? 2.1. Introduction 2.2. Direct topographic surveying 2.3. Remote digital surveying 2.4. Chapter summary References Further Reading/Resources Chapter 3: Background to Structure from Motion 3.1. Introduction 3.2. Feature Detection 3.3. Keypoint Correspondence 3.4. Identifying Geometrically Consistent Matches 3.5. Structure from Motion 3.6. Scale and Georeferencing 3.7. Optimization of Image Alignment 3.8. Clustering for Multi View Stereo 3.9. Multi View Stereo Image Matching Algorithms 3.10. Summary References Further Reading/Resources Chapter 4: Structure from Motion in practice 4.1. Introduction 4.2. Platforms 4.3. Sensors 4.4. Acquiring images and control data 4.5. Software 4.6. Point cloud viewers 4.7. Filtering 4.8. Generating digital elevation models (DEMs) from point clouds 4.9. Key issues 4.10. Chapter summary References Further reading Chapter 5: Quality assessment: quantifying error in Structure from Motion-derived topographic data 5.1. Introduction 5.2. Validation Data Sets 5.3. Validation Methods 5.4. Survey Platform 5.5. Error Metrics 5.6. Distribution of Ground Control Points 5.7. Terrain 5.8. Software 5.9. Camera 5.10. Summary References Further Reading/Resources Chapter 6: Current applications of Structure from Motion in the geosciences 6.1. Introduction 6.2. Use of SfM-MVS-derived orthophotograph mosaics 6.3. Use of SfM-MVS for 3D point clouds 6.4. Use of SfM-MVS for gridded topography 6.5. Combined orthophotograph and point cloud analysis 6.6. Crossing temporal scales: Examples of change detection to suggest process dynamics 6.7. Practitioner-based SfM-MVS 6.8. Chapter summary References Further Reading/Resources Chapter 7: Developing Structure from Motion for the geosciences: future directions 7.1. Introduction 7.2. Developments in hardware 7.3. Progressive automation of acquisition 7.4. Efficient management and manipulation of photographs 7.5. Point cloud generation and decimation 7.6. Real-time SfM-MVS and instant maps: Simultaneous Localization And Mapping (SLAM) 7.7. Augmented reality 7.8. Detection of object or surface motion: non-rigid SfM (NRSfM) 7.9. Chapter summary References Further Reading/Resources Chapter 8: Concluding recommendations 8.1. Key Recommendation 1: get under the bonnet of SfM-MVS to become more critical end-users 8.2. Key Recommendation 2: get coordinated to understand the sources and magnitudes of error 8.3. Key Recommendation 3: focus on the research question 8.4. Key Recommendation 4: focus your efforts on data processing 8.5. Key Recommendation 5: learn from other disciplines 8.6. Key Recommendation 6: harness the democratising power of SfM-MVS Index
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Structure from Motion with Multi View Stereo provides hyperscale landform models using images acquired from standard compact cameras and a network of ground control points.
Abbreviations About the companion website Chapter 1: Introduction to Structure from Motion for the geosciences 1.1. The geosciences and related disciplines 1.2. Aim and scope of this book 1.3. The time and the place 1.4. What is Structure from Motion? 1.5. Structure of this book References Chapter 2: The place of Structure from Motion: a new paradigm in topographic surveying? 2.1. Introduction 2.2. Direct topographic surveying 2.3. Remote digital surveying 2.4. Chapter summary References Further Reading/Resources Chapter 3: Background to Structure from Motion 3.1. Introduction 3.2. Feature Detection 3.3. Keypoint Correspondence 3.4. Identifying Geometrically Consistent Matches 3.5. Structure from Motion 3.6. Scale and Georeferencing 3.7. Optimization of Image Alignment 3.8. Clustering for Multi View Stereo 3.9. Multi View Stereo Image Matching Algorithms 3.10. Summary References Further Reading/Resources Chapter 4: Structure from Motion in practice 4.1. Introduction 4.2. Platforms 4.3. Sensors 4.4. Acquiring images and control data 4.5. Software 4.6. Point cloud viewers 4.7. Filtering 4.8. Generating digital elevation models (DEMs) from point clouds 4.9. Key issues 4.10. Chapter summary References Further reading Chapter 5: Quality assessment: quantifying error in Structure from Motion-derived topographic data 5.1. Introduction 5.2. Validation Data Sets 5.3. Validation Methods 5.4. Survey Platform 5.5. Error Metrics 5.6. Distribution of Ground Control Points 5.7. Terrain 5.8. Software 5.9. Camera 5.10. Summary References Further Reading/Resources Chapter 6: Current applications of Structure from Motion in the geosciences 6.1. Introduction 6.2. Use of SfM-MVS-derived orthophotograph mosaics 6.3. Use of SfM-MVS for 3D point clouds 6.4. Use of SfM-MVS for gridded topography 6.5. Combined orthophotograph and point cloud analysis 6.6. Crossing temporal scales: Examples of change detection to suggest process dynamics 6.7. Practitioner-based SfM-MVS 6.8. Chapter summary References Further Reading/Resources Chapter 7: Developing Structure from Motion for the geosciences: future directions 7.1. Introduction 7.2. Developments in hardware 7.3. Progressive automation of acquisition 7.4. Efficient management and manipulation of photographs 7.5. Point cloud generation and decimation 7.6. Real-time SfM-MVS and instant maps: Simultaneous Localization And Mapping (SLAM) 7.7. Augmented reality 7.8. Detection of object or surface motion: non-rigid SfM (NRSfM) 7.9. Chapter summary References Further Reading/Resources Chapter 8: Concluding recommendations 8.1. Key Recommendation 1: get under the bonnet of SfM-MVS to become more critical end-users 8.2. Key Recommendation 2: get coordinated to understand the sources and magnitudes of error 8.3. Key Recommendation 3: focus on the research question 8.4. Key Recommendation 4: focus your efforts on data processing 8.5. Key Recommendation 5: learn from other disciplines 8.6. Key Recommendation 6: harness the democratising power of SfM-MVS Index
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
