Structure from motion in the geosciences
著者
書誌事項
Structure from motion in the geosciences
(New analytical methods in earth and environmental science / series editors, Kurt Konhauser ... [et al.])
Wiley-Blackwell, 2016
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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. The technique is not limited in temporal frequency and can provide point cloud data comparable in density and accuracy to those generated by terrestrial and airborne laser scanning at a fraction of the cost. It therefore offers exciting opportunities to characterise surface topography in unprecedented detail and, with multi-temporal data, to detect elevation, position and volumetric changes that are symptomatic of earth surface processes. This book firstly places Structure from Motion in the context of other digital surveying methods and details the Structure from Motion workflow including available software packages and assessments of uncertainty and accuracy. It then critically reviews current usage of Structure from Motion in the geosciences, provides a synthesis of recent validation studies and looks to the future by highlighting opportunities arising from developments in allied disciplines. This book will appeal to academics, students and industry professionals because it balances technical knowledge of the Structure from Motion workflow with practical guidelines for image acquisition, image processing and data quality assessment and includes case studies that have been contributed by experts from around the world.
目次
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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