Optical flow methods

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Table of contents

1 Introduction
1.1 Problem Statement (Motivation)
1.2 Approach Chosen to Solve the Problem
1.3 Limitations
1.4 Thesis Goals and Contribution
2 Background, Definitions and Related works
2.1 Optical flow and Motion
2.2 Optical flow calculation and Aperture problem
2.3 Optical flow methods
2.4 Gaussian Pyramid of Gradients
3 Estimation of optical flow vectors
3.1 Estimated Optical flow vectors for each pyramids’ level
3.2 MSE (Mean Squared Error)
3.3 Comparing of Error Vectors in Different Pyramid Levels
4 Optical flow algorithm’s results
4.1 Capturing and Collecting best optical flow vectors
5 Event detection
5.1 Making grayscale and binary image
5.2 Segmentation and Moment calculation
5.3 Results on Events Detection
5.4 Conclusions and suggestions for future works
Appendix
1 Developing of the “PL” algorithm
1.1 Starting with making video samples
1.2 How to set input parameters
2 Calculation of error vectors (displacement vector) for each pixel
2.1 Estimated Optical flow Vectors (Red) and Calculated flow motions (Blue) with desired speed
2.2 Calculation of MSE (Mean Squared Error).
References