[CT404]: Remove non-assignment labs, move assignment labs to 'assignments'

year4/semester1/CT404: Graphics & Image Processing/labs/1. Camera Calibration/camera_P.m

@@ -1,190 +0,0 @@
-close all
-clear all
-clc
-
-filename = "rubiks2.jpg"
-num_points = 24;  % Set number of points
-
-
-% Prompt user to load data or select points manually
-choice = menu('Do you want to load points from the workspace_variables.mat file?', 'Yes', 'No');
-
-if choice == 1
-    % Load points from .mat file
-    load('workspace_variables.mat');
-
-    % Ensure the necessary variables exist in the loaded file
-    if exist('image_points', 'var') && exist('world_points', 'var')
-        disp('Points successfully loaded from workspace_variables.mat');
-    else
-        error('The loaded file does not contain the required variables "image_points" and "world_points".');
-    end
-else
-    % Proceed with manual selection if user chooses "No"
-
-    % Load and display the image
-    img = imread(filename);  % Replace with your image file path
-    imshow(img);  % Display the image
-    hold on;  % Keep the image displayed while adding markers
-
-    % Initialize matrices to store 2D and 3D homogeneous coordinates
-    image_points = zeros(num_points, 3);  % For 2D image points in homogeneous coordinates
-    world_points = zeros(num_points, 4);  % For 3D world points in homogeneous coordinates
-
-    disp('Click on the image to select 96 points and enter their 3D world coordinates.');
-
-    for i = 1:num_points
-        % Use ginput to get one imJKJKJJKJKJage point at a time
-        [x, y] = ginput(1);
-
-        % Store the 2D image coordinates in homogeneous form
-        image_points(i, :) = [x, y, 1];
-
-        % Plot the selected point on the image
-        plot(x, y, 'r+', 'MarkerSize', 8, 'LineWidth', 1.5);
-
-        % Display the current point number for reference
-        text(x, y, sprintf('  %d', i), 'Color', 'yellow', 'FontSize', 10, 'FontWeight', 'bold');
-
-        % GUI prompt for 3D world coordinates
-        prompt = sprintf('Enter the 3D world coordinates for point %d (X, Y, Z):', i);
-        title = '3D World Coordinate Input';
-        dims = [1];  % Set single row dimension for the input dialog
-        default_input = {'0', '0', '0'};  % Default values for input fields
-        answer = inputdlg({'X:', 'Y:', 'Z:'}, title, dims, default_input);
-
-        % Convert input to numeric values and store in homogeneous form
-        if ~isempty(answer)
-            world_coords = str2double(answer);  % Convert cell array of strings to numeric array
-            world_points(i, :) = [world_coords', 1];  % Store in homogeneous form [X Y Z 1]
-        else
-            error('3D coordinate input was canceled.');  % Handle case if input is canceled
-        end
-    end
-
-    % Release the hold on the image display
-    hold off;
-end
-
-% Construct the matrix A for solving P using SVD
-A = [];
-for i = 1:num_points
-    X = world_points(i, :);      % Homogeneous 3D coordinates [X Y Z 1]
-    x = image_points(i, 1);      % x-coordinate of the 2D image point
-    y = image_points(i, 2);      % y-coordinate of the 2D image point
-
-    % Build the two rows for each point
-    row1 = [zeros(1, 4), -X, y * X];
-    row2 = [X, zeros(1, 4), -x * X];
-
-    % Append the rows to A
-    A = [A; row1; row2];
-end
-
-% Compute the camera projection matrix P using SVD
-[~, ~, V] = svd(A);
-P = reshape(V(:, end), 4, 3)';  % Reshape the last column of V into a 3x4 matrix
-
-% Compute the camera center as the null space of P
-[~, ~, V_P] = svd(P);
-camera_center_h = V_P(:, end);  % Last column of V
-camera_center = camera_center_h(1:3) / camera_center_h(4);  % Convert from homogeneous
-
-% Decompose P into K and R using QR decomposition on the first 3x3 part
-M = P(:, 1:3);  % The 3x3 submatrix of P
-[Q, R] = qr(inv(M));  % Use QR decomposition
-K = inv(R);           % Intrinsic matrix
-K = K / K(3,3);       % Normalize K so that K(3,3) is 1
-R = inv(Q);           % Rotation matrix
-
-% Display computed matrices
-disp('Computed camera matrix P:');
-disp(P);
-disp('Intrinsic matrix K:');
-disp(K);
-disp('Rotation matrix R:');
-disp(R);
-disp('Camera center (in world coordinates):');
-disp(camera_center);
-
-% Visualization in 3D
-figure 1;
-scatter3(world_points(:,1), world_points(:,2), world_points(:,3), 'bo'); % Plot 3D points
-hold on;
-scatter3(camera_center(1), camera_center(2), camera_center(3), 'ro', 'filled');  % Plot camera center
-quiver3(camera_center(1), camera_center(2), camera_center(3), -R(3,1), -R(3,2), -R(3,3), 10, 'r');  % Plot principal axis
-%title('3D Points, Camera Center, and Principal Axis');
-xlabel('X');
-ylabel('Y');
-zlabel('Z');
-legend('3D Points', 'Camera Center', 'Principal Axis');
-grid on;
-hold off;
-
-% Back-project the 3D points onto the 2D image using the camera matrix P
-projected_points = P * world_points';
-
-% Convert from homogeneous coordinates to 2D by normalizing
-projected_points = projected_points ./ projected_points(3, :);
-
-% Display the original image and overlay the back-projected points
-
-% Assuming P is already computed and available
-
-% Define the points at infinity along the axes
-D_x = [1; 0; 0; 0];  % Point at infinity along X-axis
-D_y = [0; 1; 0; 0];  % Point at infinity along Y-axis
-D_z = [0; 0; 1; 0];  % Point at infinity along Z-axis
-D_o = [0; 0; 0; 1];  % World origin
-
-% Project these points using the camera projection matrix P
-image_point_infinity_x = P * D_x;
-image_point_infinity_y = P * D_y;
-image_point_infinity_z = P * D_z;
-image_point_origin = P * D_o;
-
-% Normalize the projected points to get 2D coordinates
-image_point_infinity_x = image_point_infinity_x ./ image_point_infinity_x(3);
-image_point_infinity_y = image_point_infinity_y ./ image_point_infinity_y(3);
-image_point_infinity_z = image_point_infinity_z ./ image_point_infinity_z(3);
-image_point_origin = image_point_origin ./ image_point_origin(3);
-
-
-% Display the original image and overlay the points at infinity
-figure(2);
-imshow(img);
-hold on;
-
-% Plot the actual image points in red
-scatter(image_points(:, 1), image_points(:, 2), 'ro', 'filled', 'DisplayName', 'Actual Image Points');
-
-% Plot back-projected points in green
-scatter(projected_points(1, :), projected_points(2, :), 'gx', 'filled', 'DisplayName', 'Back-Projected 3D Points');
-
-% Plot points at infinity with different markers and colors
-scatter(image_point_infinity_x(1), image_point_infinity_x(2), 'bx', 'LineWidth', 2, 'DisplayName', 'Point at Infinity (X-axis)');
-scatter(image_point_infinity_y(1), image_point_infinity_y(2), 'gx', 'LineWidth', 2, 'DisplayName', 'Point at Infinity (Y-axis)');
-scatter(image_point_infinity_z(1), image_point_infinity_z(2), 'mx', 'LineWidth', 2, 'DisplayName', 'Point at Infinity (Z-axis)');
-scatter(image_point_origin(1), image_point_origin(2), 'ko', 'filled', 'DisplayName', 'World Origin');
-
-% Draw vanishing lines from world origin to points at infinity
-plot([image_point_origin(1), image_point_infinity_x(1)], ...
-     [image_point_origin(2), image_point_infinity_x(2)], ...
-     'b--', 'LineWidth', 1.5, 'DisplayName', 'Vanishing Line (X-axis)');
-
-plot([image_point_origin(1), image_point_infinity_y(1)], ...
-     [image_point_origin(2), image_point_infinity_y(2)], ...
-     'g--', 'LineWidth', 1.5, 'DisplayName', 'Vanishing Line (Y-axis)');
-
-% Draw a line connecting points at infinity in X and Y directions
-plot([image_point_infinity_x(1), image_point_infinity_y(1)], ...
-     [image_point_infinity_x(2), image_point_infinity_y(2)], ...
-     'm--', 'LineWidth', 1.5, 'DisplayName', 'Line Between Infinity Points');
-
-% Add title
-
-% Create legend
-%legend show;  % Show legend to display all categories
-
-hold off;
-

year4/semester1/CT404: Graphics & Image Processing/labs/1. Camera Calibration/latex/assignment.tex

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-%! TeX program = lualatex
-\documentclass[a4paper]{article} 
-
-% packages
-\usepackage{microtype}      % Slightly tweak font spacing for aesthetics
-\usepackage[english]{babel} % Language hyphenation and typographical rules
-\usepackage[final, colorlinks = true, urlcolor = black, linkcolor = black]{hyperref} 
-\usepackage{changepage}     % adjust margins on the fly
-
-\usepackage{fontspec}
-\setmainfont{EB Garamond}
-\setmonofont[Scale=MatchLowercase]{Deja Vu Sans Mono}
-
-\usepackage{minted}
-\usemintedstyle{algol_nu}
-\usepackage{xcolor}
-
-\usepackage{pgfplots}
-\pgfplotsset{width=\textwidth,compat=1.9}
-
-\usepackage{caption}
-\newenvironment{code}{\captionsetup{type=listing}}{}
-\captionsetup[listing]{skip=0pt}
-\setlength{\abovecaptionskip}{5pt}
-\setlength{\belowcaptionskip}{5pt}
-
-\usepackage[yyyymmdd]{datetime}
-\renewcommand{\dateseparator}{--}
-
-\usepackage{titlesec}
-% \titleformat{\section}{\LARGE\bfseries}{}{}{}[\titlerule]
-% \titleformat{\subsection}{\Large\bfseries}{}{0em}{}
-% \titlespacing{\subsection}{0em}{-0.7em}{0em}
-%
-% \titleformat{\subsubsection}{\large\bfseries}{}{0em}{$\bullet$ }
-% \titlespacing{\subsubsection}{1em}{-0.7em}{0em}
-
-% margins
-\addtolength{\hoffset}{-2.25cm}
-\addtolength{\textwidth}{4.5cm}
-\addtolength{\voffset}{-3.25cm}
-\addtolength{\textheight}{5cm}
-\setlength{\parskip}{0pt}
-\setlength{\parindent}{0in}
-% \setcounter{secnumdepth}{0}
-
-\begin{document}
-\hrule \medskip
-\begin{minipage}{0.295\textwidth} 
-    \raggedright
-    \footnotesize 
-    \begin{tabular}{@{}l l} % Define a two-column table with left alignment
-        Name: & Andrew Hayes \\
-        Student ID: & 21321503 \\
-    \end{tabular}
-\end{minipage}
-\begin{minipage}{0.4\textwidth} 
-    \centering 
-    \vspace{0.4em}
-    \LARGE 
-    \textsc{ct404} \\ 
-\end{minipage}
-\begin{minipage}{0.295\textwidth} 
-    \raggedleft
-    \footnotesize 
-    \begin{tabular}{@{}l l} % Define a two-column table with left alignment
-        Name: & Maxwell Maia \\
-        Student ID: & 21236277 \\
-    \end{tabular}
-\end{minipage}
-\smallskip
-\hrule 
-\begin{center}
-    \normalsize
-    Lab Assignment 1: Camera Callibration
-\end{center}
-\hrule
-
-\section{\textit{P}-Matrix Estimation Using Provided Code}
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/1.1.png}
-    \caption{ Command window output showing he computed camera matrix $P$, the intrinsic matrix $K$, \& the rotation matrix $R$ }
-\end{figure}
-
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/1.2.png}
-    \caption{ The 3D plot showing the camera center, the world points, \& the principal axis }
-\end{figure}
-
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/1.3.png}
-    \caption{ The image with projected 3D points \& vanishing lines }
-\end{figure}
-
-\section{Using Your Own Image from Your Camera for \textit{P}-Matrix Estimation}
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/2.1.png}
-    \caption{ Command window output showing he computed camera matrix $P$, the intrinsic matrix $K$, \& the rotation matrix $R$ }
-\end{figure}
-
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/2.2.png}
-    \caption{ The 3D plot showing the camera center, the world points, \& the principal axis }
-\end{figure}
-
-\begin{figure}[H]
-    \centering
-    \includegraphics[width=\textwidth]{./images/2.3.png}
-    \caption{ The image with projected 3D points \& vanishing lines }
-\end{figure}
-
-\section{Experiment \& Reflect}
-\subsection{How does increasing the number of points affect the accuracy \& stability of the \textit{P}-matrix estimation?}
-As the number of control points increased, the accuracy and stability of the estimated P Matrix improved. With 12 points, we observed discrepancies in the back-projected 3D points, while results with 40 points were far more consistent. The intrinsic and rotation matrices derived from the P Matrix appeared less sensitive to noise with more points, enhancing the reliability of the calibration.
-
-\subsection{Is there a noticeable difference in the accuracy of the back-projection when using fewer points versus more points?}
-Using fewer points (e.g., 12) resulted in higher deviations in back-projected points compared to their actual image locations. With 40 points, the back-projection closely matched the real-world setup, minimizing errors.
-
-\subsection{What challenges did you encounter when manually selecting points \& entering 3D world coordinates?}
-The primary challenge that we faced when manually entering selecting the points was the precision: it was extremely difficult to precisely select the correct points due to the imprecision of the mouse as a selection device, human error, and a lack of fine-grain zoom control in the MATLAB UI.
-\\\\
-We also found the process of manually entering the points very time-consuming and error-prone.
-If we mis-clicked a point or accidentally entered in the wrong world coordinate, it would greatly damage the accuracy of the entire calibration and we would be forced to start over again.
-
-\end{document}