Question

在物体检测文献中，通常使用分类器和滑动窗口方法来检测图像中物体的存在，该方法返回一组检测窗口，并使用非最大抑制来解析检测重叠。

有人可以解释在这些检测窗口上执行非最大抑制的算法。

由于

Answer 1

引自http://www.di.ens.fr/willow/events/cvml2012/materials/practical-detection/

图像块的扫描窗口样式分类通常导致目标对象周围的多个响应。处理此问题的标准做法是使用局部最大置信度得分（非最大值抑制或NMS）去除检测附近的任何检测器响应。 NMS通常应用于图像中的所有检测，其置信度高于特定阈值。尝试针对不同阈值和不同图像进行NMS人脸检测：

同样在这里http://www.ens-lyon.fr/LIP/Arenaire/ERVision/detection_exercise_solution.m你可以找到一个可以完成所有事情的matlab程序 - 检测窗口上的检测和NMS

对检测窗口进行非最大抑制的代码是

%%%%%%%%%%%%%%% **************************************************************
%%%%%%%%%%%%%%% **************************************************************
%%%%%%%%%%%%%%% *                                                            *
%%%%%%%%%%%%%%% *                       EXERCISE 3:                          *
%%%%%%%%%%%%%%% *                                                            *
%%%%%%%%%%%%%%% *        Non-maxima suppression of multiple responses        *
%%%%%%%%%%%%%%% *                                                            *
%%%%%%%%%%%%%%% **************************************************************
%%%%%%%%%%%%%%% **************************************************************
%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%% Scanning-window style classification of image patches typically
%%%%%%%%%%%%%%% results in many multiple responses around the target object.
%%%%%%%%%%%%%%% A standard practice to deal with this is to remove any detector
%%%%%%%%%%%%%%% responses in the neighborhood of detections with locally maximal
%%%%%%%%%%%%%%% confidence scores (non-maxima suppression or NMS). NMS is
%%%%%%%%%%%%%%% usually applied to all detections in the image with confidence
%%%%%%%%%%%%%%% above certain threshold.
%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%% TODO:
%%%%%%%%%%%%%%% 3.1 Try out different threshold values to pre-selected windows
%%%%%%%%%%%%%%%     passed to the NMS stage, see parameter 'confthresh' below.
%%%%%%%%%%%%%%% 3.2 Try out different threshold values for NMS detections,
%%%%%%%%%%%%%%%     see parameter 'confthreshnms'
%%%%%%%%%%%%%%% 3.3 Try detection and with different thresholds for different
%%%%%%%%%%%%%%%     included images: 'img1.jpg', 'img2.jpg', 'img3.jpg', 'img4.jpg'
%%%%%%%%%%%%%%% 
confthresh=0;
indsel=find(conf>confthresh);
[nmsbbox,nmsconf]=prunebboxes(bbox(indsel,:),conf(indsel),0.2);


%%%%%%%%%%%%%%% display detections above threshold after non-max suppression
%%%%%%%%%%%%%%% 
confthreshnms=1;
clf, showimage(img)
indsel=find(nmsconf>confthreshnms);
showbbox(nmsbbox(indsel,:),[1 1 0],regexp(num2str(nmsconf(indsel)'),'\d+\.\d+','match'));
title(sprintf('%d NMS detections above threshold %1.3f',size(nmsbbox,1),confthreshnms),'FontSize',14)
fprintf('press a key...'), pause, fprintf('\n')

您可以在第一个链接中找到所有相关功能。

检测窗口的非最大抑制

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