Kalman Filter Implementation for Object Tracking

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Added on  2024/05/23

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This document details the implementation of a Kalman filter for object tracking in a video sequence. The algorithm is designed to estimate the position of a moving object, specifically a ball, by incorporating noisy measurements from a camera. The implementation involves several key steps: 1) Kalman filter prediction and update, 2) Object detection using image processing techniques, 3) Extraction of the ball's center and radius, and 4) Background subtraction to isolate the ball from the surrounding environment. The document includes detailed code snippets, flowcharts, and illustrative figures to explain the process. The results demonstrate the effectiveness of the Kalman filter in providing accurate and robust object tracking, even in the presence of noise and uncertainties.

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Table of contents
Implelenting Kalman algorithm.............................................................................................................2
Kalman implementation....................................................................................................................2
Detecting of position of moving object.............................................................................................5
Extracting the ball, its center and radius and avoiding background..................................................6
Flow chart..............................................................................................................................................7
List of figures
Figure 1: kalman part1...........................................................................................................................2
Figure 2: Kalman part2..........................................................................................................................3
Figure 3: Kalman part3..........................................................................................................................4
Figure 4: Detecting ball..........................................................................................................................5
Figure 5: extractball part1.....................................................................................................................6
Figure 6: extractball part2.....................................................................................................................7
Figure 7: Kalman flow chart...................................................................................................................8
Figure 8: Tracking ball flowchart............................................................................................................9
Figure 9: extracting ball flowchart.......................................................................................................10
Figure 10: output image......................................................................................................................11
Figure 11: approximation detection....................................................................................................12

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Implelenting Kalman algorithm
Kalman implementation
Figure 1: kalman part1
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Figure 2: Kalman part2
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Figure 3: Kalman part3
This code will load the image files and predict the position of the moving object. I have
implemented the relevant logic to estimate the noise within the moving object.

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Detecting of position of moving object
Figure 4: Detecting ball
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Extracting the ball, its center and radius and avoiding background
Figure 5: extractball part1
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Figure 6: extractball part2
Flow chart

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Figure 7: Kalman flow chart
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Figure 8: Tracking ball flowchart
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Figure 9: extracting ball flowchart

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Output of the code
Figure 10: output image
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Figure 11: approximation detection
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