求pawcs的matlab代码

Question

求pawcs的matlab代码！！
只能找到c++的代码，但是想要matlab的
《A_Self-Adjusting_Approach_to_Change_Detection_Based_on_Background_Word_Consensus》这个文章的方法

Answer 1

可以尝试根据该论文中描述的算法步骤自行实现MATLAB代码。
以下是一个基本的框架，可用作开始：

function [foregroundMask] = pawcs(imageSequence)
    % 初始化参数
    numGaussians = 3;  % 高斯模型数量
    alpha = 0.01;  % 学习速率
    T = 0.9;  % 阈值

    % 初始化背景模型和权重
    backgroundModel = cell(numGaussians, 1);
    weights = zeros(numGaussians, 1);

    % 处理图像序列
    for i = 1:size(imageSequence, 4)
        frame = imageSequence(:, :, :, i);
        
        % 初始化前景掩码
        foregroundMask = zeros(size(frame, 1), size(frame, 2));

        % 对每个像素进行处理
        for y = 1:size(frame, 1)
            for x = 1:size(frame, 2)
                pixelValue = double(squeeze(frame(y, x, :)));

                % 检测前景像素
                isForegroundPixel = detectForegroundPixel(pixelValue, backgroundModel, weights, T);

                if isForegroundPixel
                    foregroundMask(y, x) = true;
                end

                % 更新背景模型和权重
                updateBackgroundModel(pixelValue, backgroundModel, weights, alpha);
            end
        end

        % 显示结果图像（可选）
        imshow(foregroundMask);
        pause(0.01);
    end
end

function isForegroundPixel = detectForegroundPixel(pixelValue, backgroundModel, weights, T)
    isForegroundPixel = false;

    for i = 1:numel(backgroundModel)
        gaussianMean = backgroundModel{i}.mean;
        gaussianCovarianceMatrixInverse = inv(backgroundModel{i}.covarianceMatrix);

        distanceSquaredThreshold = chi2inv(T * weights(i), numel(pixelValue));

        distanceSquaredToMean = sum((pixelValue - gaussianMean) .* (pixelValue - gaussianMean));
        
        if distanceSquaredToMean < distanceSquaredThreshold
            isForegroundPixel= true;
            break;
        end
    end    
end

function updateBackgroundModel(pixelValue, backgroundModel, weights,alpha)
   ...
   % 根据论文中的公式更新背景模型和权重 
   ...
end

% 调用pawcs函数并传入图像序列作为输入参数，例如：
imageSequence = ...;   % 图像序列（H x W x C x N）
foregroundMaskSequence= pawcs(imageSequence);