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Computer Science - Image Processing | 3D Computer Vision - Efficient Methods and Applications

3D Computer Vision

Efficient Methods and Applications

Wöhler, Christian

2009, XVI, 385p. 170 illus..


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  • Provides an overview of the current state of the art in the field of three-dimensional computer vision
  • Offers a unified description of photogrammetric and computer vision approaches
  • Gives an in-depth presentation of three-dimensional scene analysis and surface reconstruction, pose estimation, and motion analysis

This book provides an introduction to the foundations of three-dimensional computer vision and describes recent contributions to the field. Geometric methods include linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and flexible objects. Photometric techniques evaluate the intensity distribution in the image to infer three-dimensional scene structure, while real-aperture approaches exploit the behavior of the point spread function. It is shown how the integration of several methods increases reconstruction accuracy and robustness. Applications scenarios include industrial quality inspection, metrology, human-robot-interaction, and remote sensing.

Content Level » Professional/practitioner

Keywords » 3D - 3D graphics - Bundle adjustment - Computer graphics - Computer vision - Industrial metrology - Photogrammetry - Remote sensing - Robotics

Related subjects » Image Processing - Media Design - Theoretical Computer Science

Table of contents 

Methods of 3D Computer Vision.- Geometric Approaches to Three-dimensional Scene Reconstruction.- Photometric Approaches to Three-dimensional Scene Reconstruction.- Real-aperture Approaches to Three-dimensional Scene Reconstruction.- Integrated Frameworks for Three-dimensional Scene Reconstruction.- Application Scenarios.- Applications to Industrial Quality Inspection.- Applications to Safe Human–Robot Interaction.- Applications to Lunar Remote Sensing.- Conclusion.

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