提取视频中的特征点、进行特征点匹配最后绘制结构振动位移曲线的matlab代码

以下是提取视频中的特征点、进行特征点匹配最后绘制结构振动位移曲线的MATLAB代码：

%% 读取视频文件
v = VideoReader('example_video.mp4');

%% 初始化变量
prev_frame = [];
prev_points = [];
total_points = [];
total_displacements = [];

%% 循环处理每一帧
while hasFrame(v)
    % 读取当前帧
    curr_frame = readFrame(v);
    curr_frame_gray = rgb2gray(curr_frame);
    
    % 如果是第一帧，则跳过特征点提取和匹配
    if isempty(prev_frame)
        prev_frame = curr_frame_gray;
        continue;
    end
    
    % 提取特征点
    curr_points = detectSURFFeatures(curr_frame_gray);
    
    % 如果没有提取到足够的特征点，则跳过特征点匹配
    if curr_points.Count < 10
        prev_frame = curr_frame_gray;
        prev_points = curr_points;
        continue;
    end
    
    % 特征点匹配
    [curr_features, curr_points] = extractFeatures(curr_frame_gray, curr_points);
    [prev_features, prev_points] = extractFeatures(prev_frame, prev_points);
    index_pairs = matchFeatures(curr_features, prev_features);
    
    % 如果没有匹配到足够的特征点，则跳过位移计算
    if size(index_pairs, 1) < 10
        prev_frame = curr_frame_gray;
        prev_points = curr_points;
        continue;
    end
    
    % 计算位移
    curr_matched_points = curr_points(index_pairs(:, 1));
    prev_matched_points = prev_points(index_pairs(:, 2));
    displacements = curr_matched_points.Location - prev_matched_points.Location;
    total_displacements(end+1) = mean(sqrt(sum(displacements.^2, 2)));
    total_points(end+1) = curr_points.Count;
    
    % 更新上一帧的信息
    prev_frame = curr_frame_gray;
    prev_points = curr_points;
end

%% 绘制振动位移曲线
plot(total_points, total_displacements);
xlabel('Number of detected features');
ylabel('Average displacement (pixels)');

注意：此代码仅供参考，具体实现可能需要根据实际情况进行调整。另外，提取特征点和匹配特征点的方法可以根据实际需求进行选择，本代码中使用的是SURF算法。