Scene Reconstruction Pose Estimation and Tracking

Rustam Stolkin

• Publisher: IntechOpen
• Year: 2007
• Print ISBN:
  9783902613066
• eBook ISBN:
  9789535158097
• Topic: Computer Science
• Subtopic: Optical Data Processing
• Index: Computer Science

This book reports recent advances in the use of pattern recognition techniques for computer and robot vision. The sciences of pattern recognition and computational vision have been inextricably intertwined since their early days, some four decades ago with the emergence of fast digital computing. All computer vision techniques could be regarded as a form of pattern recognition, in the broadest sense of the term. Conversely, if one looks through the contents of a typical international pattern recognition conference proceedings, it appears that the large majority (perhaps 70-80%) of all pattern recognition papers are concerned with the analysis of images. In particular, these sciences overlap in areas of low level vision such as segmentation, edge detection and other kinds of feature extraction and region identification, which are the focus of this book.

Table of contents

• Scene Reconstruction Pose Estimation and Tracking
• Preface
• Contents
• 1. Real-Time Object Segmentation of the Disparity Map Using Projection-Based Region Merging
• 2. A Novel Omnidirectional Stereo Vision System via a Single Camera1
• 3. Stereo Vision Camera Pose Estimation for On-Board Applications
• 4. Correcting Radial Distortion of Cameras with Wide Angle Lens Using Point Correspondences
• 5. Soft Computing Applications in Robotic Vision Systems
• 6. Analysis of Video-Based 3D Tracking Accuracy by Using Electromagnetic Tracker as a Reference
• 7. Photorealistic 3D Model Reconstruction based on the Consistency of Object Surface Reflectance Measured by the Voxel Mask
• 8. Collaborative MR Workspace with Shared 3D Vision Based on Stereo Video Transmission
• 9. Multiple Omnidirectional Vision System and Multilayered Fuzzy Behavior Control for Autonomous Mobile Robot
• 10. A Tutorial on Parametric Image Registration
• 11. A Pseudo Stereo Vision Method using Asynchronous Multiple Cameras
• 12. Real-Time 3-D Environment Capture Systems
• 13. Projective Rectification with Minimal Geometric Distortion
• 14. Non-rigid Stereo-motion
• 15. Continuous Machine Learning in Computer Vision – Tracking with Adaptive Class Models
• 16. A Sensors System for Indoor Localisation of a Moving Target Based on Infrared Pattern Recognition
• 17. Pseudo Stereovision System (PSVS): AMonocular Mirror-based Stereovision System
• 18. Tracking of Facial Regions Using Active ShapeModels and Adaptive Skin Color Modeling
• 19. Bimanual Hand Tracking based on AR-KLT
• 20. An Introduction to Model-Based PoseEstimation and 3-D Tracking Techniques
• 21. Global Techniques for Edge based StereoMatching
• 22. Local Feature Selection andGlobal Energy Optimization in Stereo
• 23. A Learning Approach for Adaptive ImageSegmentation
• 24. A Novel Omnidirectional Stereo Vision System with a Single Camera1
• 25. Image Processing Techniques for Unsupervised Pattern Classification
• 26. Articulated Hand Tracking by ICA-based Hand Model and Multiple Cameras
• 27. Biologically Motivated Vergence Control System Based on Stereo Saliency Map Model