Motion Estimation Lecture

Abstract

Motion estimation principals will be analyzed. Initiating form 2D and 3D motion models, displacement estimation as well as quality metrics for motion estimation will subsequently be detailed. One of the basic motion estimation techniques, namely block matching, will also be presented, along with three alternative, faster methods. A good overview of deep neural notion estimation will be presented. Phase correlation will be described, next followed by optical flow equation methods. Finally, a brief introduction to object detection and tracking will conclude the lecture.

 

Forward and backward 2D motion estimation.

Motion fields.

Motion-estimation-v3.4.1-Summary

Understanding Questionnaire

https://docs.google.com/forms/motion-estimation

Tutorial Exercises

1. 3D Point Projection and Motion Tutorial Exercise
2. Affine Transformation Motion Tutorial Exercise
3. Exhaustive Block Matching Tutorial Exercise
4. Hierarchical Block Matching Complexity Tutorial Exercise
5. Hierarchical Block Matching Tutorial Exercise
6. Motion and Fourier Transform Tutorial Exercise
7. Orthographic Projection and 2D Motion
8. Perspective Projection and 2D Motion