3D Dynamic Scene Analysis [E-Book] : A Stereo Based Approach / by Zhengyou Zhang, Olivier Faugeras.
Zhang, Zhengyou, (author)
Faugeras, Olivier, (author)
Berlin, Heidelberg : Springer, 1992
XI, 300 p. online resource.
englisch
9783642581489
10.1007/978-3-642-58148-9
Springer Series in Information Sciences ; 27
Full Text
Table of Contents:
  • 1. Introduction
  • 1.1 Brief Overview of Motion Analysis
  • 1.2 Statement of the “Motion from Stereo” Problem
  • 1.3 Organization of The Book
  • 2. Uncertainty Manipulation and Parameter Estimation
  • 2.1 Probability Theory and Geometric Probability
  • 2.2 Parameter Estimation
  • 2.3 Summary
  • 2.4 Appendix: Least-Squares Techniques
  • 3. Reconstruction of 3D Line Segments
  • 3.1 Why 3D Line Segments
  • 3.2 Stereo Calibration
  • 3.3 Algorithm of the Trinocular Stereovision
  • 3.4 Reconstruction of 3D Segments
  • 3.5 Summary
  • 4. Representations of Geometric Objects
  • 4.1 Rigid Motion
  • 4.2 3D Line Segments
  • 4.3 Summary
  • 4.4 Appendix: Visualizing Uncertainty
  • 5. A Comparative Study of 3D Motion Estimation
  • 5.1 Problem Statement
  • 5.2 Extended Kalman Filter Approaches
  • 5.3 Minimization Techniques
  • 5.4 Analytical Solution
  • 5.5 Kim and Aggarwal’s method
  • 5.6 Experimental Results
  • 5.7 Summary
  • 5.8 Appendix: Motion putation Using the New Line Segment Representation
  • 6. Matching and Rigidity Constraints
  • 6.1 Matching as a Search
  • 6.2 Rigidity Constraint
  • 6.3 Completeness of the Rigidity Constraints
  • 6.4 Error Measurements inn the Constraints
  • 6.5 Other Formalisms Rigidity Constraints
  • 6.6 Summary
  • 7. Hypothesize-and-Verify Method for Two 3D View Motion Analysis
  • 7.1 General Presentation
  • 7.2 Generating Hypotheses
  • 7.3 Verifying Hypothesis
  • 7.4 Matching Noisy Segments
  • 7.5 Experimental Results
  • 7.6 Summary
  • 7.7 Appendix: Transforming a 3D Line Segment
  • 8. Further Considerations on Reducing Complexity
  • 8.1 Sorting Data Features
  • 8.2 “Good-Enough” Method
  • 8.3 Speeding Up the Hypothesis Generation Process Through Grouping
  • 8.4 Finding Clusters Based on Proximity
  • 8.5 Finding Planes
  • 8.6 Experimental Results
  • 8.6.1 Grouping Results
  • 8.6.2 Motion Results
  • 8.7 Conclusion
  • 9. Multiple Object Motions
  • 9.1 Multiple Object Motions
  • 9.2 Influence of Egomotion on Observed Object Motion
  • 9.3 Experimental Results
  • 9.4 Summary
  • 10. Object Recognition and Localization
  • 10.1 Model-Based Object Recognition
  • 10.2 Adapting the Motion-Determination Algorithm
  • 10.3 Experimental Result
  • 10.4 Summary
  • 11. Calibrating a Mobile Robot and Visual Navigation
  • 11.1 The INRIA Mobile Robot
  • 11.2 Calibration Problem
  • 11.3 Navigation Problem
  • 11.4 Experimental Results
  • 11.5 Integrating Motion Information from Odometry
  • 11.6 Summary
  • 12. Fusing Multiple 3D Frames
  • 12.1 System Description
  • 12.2 Fusing Segments from Multiple Views
  • 12.3 Experimental Results
  • 12.4 Summary
  • 13. Solving the Motion Tracking Problem: A Framework
  • 13.1 Previous Work
  • 13.2 Position of the Problem and Primary Ideas
  • 13.3 Solving the Motion Tracking Problem: A Framework
  • 13.4 Splitting or Merging
  • 13.5 Handling Abrupt Changes of Motion
  • 13.6 Discussion
  • 13.7 Summary
  • 14. Modeling and Estimating Motion Kinematics
  • 14.1 The Classical Kinematic Model
  • 14.2 Closed-Form Solutions for Some Special Motions
  • 14.2.1 Motion with Constant Angular and Translational Velocities
  • 14.2.2 Motion with Constant Angular Velocity and Constant Translational Acceleration
  • 14.2.3 Motion with Constant Angular Velocity and General Translational Velocity
  • 14.2.4 Discussions
  • 14.3 Relation with Two-View Motion Analysis
  • 14.4 Formulation for the EKF Approach
  • 14.5 Linearized Kinematic Model
  • 14.6 Summary
  • 15. Implementation Details and Experimental Results
  • 15.1 Matching Segments
  • 15.2 Support of Existence
  • 15.3 Algorithm of the Token Tracking Process
  • 15.4 Grouping Tokens into Objects
  • 15.5 Experimental Results
  • 15.5.1 Synthetic Data
  • 15.6 Summary
  • 16. Conclusions and Perspectives
  • 16.1 Summary
  • 16.2 Perspectives
  • Appendix: Vector Manipulation and Differentiation
  • A.1 Manipulation of Vectors
  • A.2 Differentiation of Vectors
  • References.