非极大值抑制算法

来源：互联网发布：smo算法 python实现编辑：程序博客网时间：2024/05/29 19:19

出处：http://www.cnblogs.com/liekkas0626/p/5219244.html

1. 算法原理

非极大值抑制算法（Non-maximum suppression, NMS）的本质是搜索局部极大值，抑制非极大值元素。

2. 3邻域情况下NMS的实现

3邻域情况下的NMS即判断一维数组I[W]的元素I[i](2<=i<=W-1)是否大于其左邻元素I[i-1]和右邻元素I[i+1]，算法流程如下图所示：

a. 算法流程3-5行判断当前元素是否大于其左邻与右邻元素，如符合条件，该元素即为极大值点。对于极大值点I[i]，已知I[i]>I[i+1]，故无需对i+1位置元素做进一步处理，直接跳至i+2位置，对应算法流程第12行。

b. 若元素I[i]不满足算法流程第3行判断条件，将其右邻I[i+1]作为极大值候选，对应算法流程第7行。采用单调递增的方式向右查找，直至找到满足I[i]>I[i+1]的元素，若i<=W-1，该点即为极大值点，对应算法流程第10-11行。

3. NMS在物体检测中的应用

物体检测中应用NMS算法的主要目的是消除多余（交叉重复）的窗口，找到最佳物体检测位置。

如上图所示，人脸检测中，虽然每个窗口均检测到人脸，但仅需给出一个最有可能表征人脸的窗口。

function pickLocate = nms(boxes, overlap) % Non-maximum suppression.% In object detect algorithm, select high score detections and skip windows% covered by a previously selected detection.%% input - boxes : object detect windows.%                 xMin yMin xMax yMax score.%         overlap : suppression threshold.% output - pickLocate : number of local maximum score. boxes = double(boxes); if isempty(boxes)    pickLocate = [];else    xMin = boxes(:, 1);    yMin = boxes(:, 2);    xMax = boxes(:, 3);    yMax = boxes(:, 4);         s = boxes(:, end);         % area of every detected windows.    area = (xMax - xMin + 1) .* (yMax - yMin + 1);         % sort detected windows based on the score.    [vals, I] = sort(s);         pickLocate = [];    while ~isempty(I)        last = length(I);        i = I(last);                 pickLocate = [pickLocate; i];        suppress = [last];                 for pos = 1 : last - 1            j = I(pos);                          % covered area.            xx1 = max(xMin(i), xMin(j));            yy1 = max(yMin(i), yMin(j));            xx2 = min(xMax(i), xMax(j));            yy2 = min(yMax(i), yMax(j));                         w = xx2 - xx1 + 1;            h = yy2 - yy1 + 1;                         if ((w > 0) && (h > 0))                % compute overlap.                o = w * h / min(area(i), area(j));                                 if (o > overlap)                    suppress = [suppress; pos];                end            end                         % xx1 = max(x1(i), x1(I(1:last-1)));            % yy1 = max(y1(i), y1(I(1:last-1)));            % xx2 = min(x2(i), x2(I(1:last-1)));            % yy2 = min(y2(i), y2(I(1:last-1)));                         % w = max(0.0, xx2-xx1+1);            % h = max(0.0, yy2-yy1+1);                         % inter = w.*h;            % o = inter ./ (area(i) + area(I(1:last-1)) - inter);                         % saving the windows which o less than threshold.            % I = I(o <= overlap);        end        I(suppress) = [];    endend

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