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added OpenSURF based object recognition

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1 parent ade82c9 commit 7ecbb06609279c868d5718f3406cf92696646c16 @AmmarkoV committed Apr 21, 2012
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BIN VisualCortex/ObjectRecogntion/box.png
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BIN VisualCortex/ObjectRecogntion/box_in_scene.png
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BIN VisualCortex/ObjectRecogntion/find_obj
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321 VisualCortex/ObjectRecogntion/find_obj.cpp
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+/*
+ * A Demo to OpenCV Implementation of SURF
+ * Further Information Refer to "SURF: Speed-Up Robust Feature"
+ * Author: Liu Liu
+ * liuliu.1987+opencv@gmail.com
+ */
+#include "opencv2/objdetect/objdetect.hpp"
+#include "opencv2/features2d/features2d.hpp"
+#include "opencv2/highgui/highgui.hpp"
+#include "opencv2/calib3d/calib3d.hpp"
+#include "opencv2/imgproc/imgproc_c.h"
+
+#include <iostream>
+#include <vector>
+#include <stdio.h>
+
+using namespace std;
+void help()
+{
+ printf(
+ "This program demonstrated the use of the SURF Detector and Descriptor using\n"
+ "either FLANN (fast approx nearst neighbor classification) or brute force matching\n"
+ "on planar objects.\n"
+ "Usage:\n"
+ "./find_obj <object_filename> <scene_filename>, default is box.png and box_in_scene.png\n\n");
+ return;
+}
+
+// define whether to use approximate nearest-neighbor search
+#define USE_FLANN
+
+
+IplImage* image = 0;
+
+double
+compareSURFDescriptors( const float* d1, const float* d2, double best, int length )
+{
+ double total_cost = 0;
+ assert( length % 4 == 0 );
+ for( int i = 0; i < length; i += 4 )
+ {
+ double t0 = d1[i ] - d2[i ];
+ double t1 = d1[i+1] - d2[i+1];
+ double t2 = d1[i+2] - d2[i+2];
+ double t3 = d1[i+3] - d2[i+3];
+ total_cost += t0*t0 + t1*t1 + t2*t2 + t3*t3;
+ if( total_cost > best )
+ break;
+ }
+ return total_cost;
+}
+
+
+int
+naiveNearestNeighbor( const float* vec, int laplacian,
+ const CvSeq* model_keypoints,
+ const CvSeq* model_descriptors )
+{
+ int length = (int)(model_descriptors->elem_size/sizeof(float));
+ int i, neighbor = -1;
+ double d, dist1 = 1e6, dist2 = 1e6;
+ CvSeqReader reader, kreader;
+ cvStartReadSeq( model_keypoints, &kreader, 0 );
+ cvStartReadSeq( model_descriptors, &reader, 0 );
+
+ for( i = 0; i < model_descriptors->total; i++ )
+ {
+ const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr;
+ const float* mvec = (const float*)reader.ptr;
+ CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader );
+ CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
+ if( laplacian != kp->laplacian )
+ continue;
+ d = compareSURFDescriptors( vec, mvec, dist2, length );
+ if( d < dist1 )
+ {
+ dist2 = dist1;
+ dist1 = d;
+ neighbor = i;
+ }
+ else if ( d < dist2 )
+ dist2 = d;
+ }
+ if ( dist1 < 0.6*dist2 )
+ return neighbor;
+ return -1;
+}
+
+void
+findPairs( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors,
+ const CvSeq* imageKeypoints, const CvSeq* imageDescriptors, vector<int>& ptpairs )
+{
+ int i;
+ CvSeqReader reader, kreader;
+ cvStartReadSeq( objectKeypoints, &kreader );
+ cvStartReadSeq( objectDescriptors, &reader );
+ ptpairs.clear();
+
+ for( i = 0; i < objectDescriptors->total; i++ )
+ {
+ const CvSURFPoint* kp = (const CvSURFPoint*)kreader.ptr;
+ const float* descriptor = (const float*)reader.ptr;
+ CV_NEXT_SEQ_ELEM( kreader.seq->elem_size, kreader );
+ CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
+ int nearest_neighbor = naiveNearestNeighbor( descriptor, kp->laplacian, imageKeypoints, imageDescriptors );
+ if( nearest_neighbor >= 0 )
+ {
+ ptpairs.push_back(i);
+ ptpairs.push_back(nearest_neighbor);
+ }
+ }
+}
+
+
+void
+flannFindPairs( const CvSeq*, const CvSeq* objectDescriptors,
+ const CvSeq*, const CvSeq* imageDescriptors, vector<int>& ptpairs )
+{
+ int length = (int)(objectDescriptors->elem_size/sizeof(float));
+
+ cv::Mat m_object(objectDescriptors->total, length, CV_32F);
+ cv::Mat m_image(imageDescriptors->total, length, CV_32F);
+
+
+ // copy descriptors
+ CvSeqReader obj_reader;
+ float* obj_ptr = m_object.ptr<float>(0);
+ cvStartReadSeq( objectDescriptors, &obj_reader );
+ for(int i = 0; i < objectDescriptors->total; i++ )
+ {
+ const float* descriptor = (const float*)obj_reader.ptr;
+ CV_NEXT_SEQ_ELEM( obj_reader.seq->elem_size, obj_reader );
+ memcpy(obj_ptr, descriptor, length*sizeof(float));
+ obj_ptr += length;
+ }
+ CvSeqReader img_reader;
+ float* img_ptr = m_image.ptr<float>(0);
+ cvStartReadSeq( imageDescriptors, &img_reader );
+ for(int i = 0; i < imageDescriptors->total; i++ )
+ {
+ const float* descriptor = (const float*)img_reader.ptr;
+ CV_NEXT_SEQ_ELEM( img_reader.seq->elem_size, img_reader );
+ memcpy(img_ptr, descriptor, length*sizeof(float));
+ img_ptr += length;
+ }
+
+ // find nearest neighbors using FLANN
+ cv::Mat m_indices(objectDescriptors->total, 2, CV_32S);
+ cv::Mat m_dists(objectDescriptors->total, 2, CV_32F);
+ cv::flann::Index flann_index(m_image, cv::flann::KDTreeIndexParams(4)); // using 4 randomized kdtrees
+ flann_index.knnSearch(m_object, m_indices, m_dists, 2, cv::flann::SearchParams(64) ); // maximum number of leafs checked
+
+ int* indices_ptr = m_indices.ptr<int>(0);
+ float* dists_ptr = m_dists.ptr<float>(0);
+ for (int i=0;i<m_indices.rows;++i) {
+ if (dists_ptr[2*i]<0.6*dists_ptr[2*i+1]) {
+ ptpairs.push_back(i);
+ ptpairs.push_back(indices_ptr[2*i]);
+ }
+ }
+}
+
+
+/* a rough implementation for object location */
+int
+locatePlanarObject( const CvSeq* objectKeypoints, const CvSeq* objectDescriptors,
+ const CvSeq* imageKeypoints, const CvSeq* imageDescriptors,
+ const CvPoint src_corners[4], CvPoint dst_corners[4] )
+{
+ double h[9];
+ CvMat _h = cvMat(3, 3, CV_64F, h);
+ vector<int> ptpairs;
+ vector<CvPoint2D32f> pt1, pt2;
+ CvMat _pt1, _pt2;
+ int i, n;
+
+#ifdef USE_FLANN
+ flannFindPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
+#else
+ findPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
+#endif
+
+ n = (int)(ptpairs.size()/2);
+ if( n < 4 )
+ return 0;
+
+ pt1.resize(n);
+ pt2.resize(n);
+ for( i = 0; i < n; i++ )
+ {
+ pt1[i] = ((CvSURFPoint*)cvGetSeqElem(objectKeypoints,ptpairs[i*2]))->pt;
+ pt2[i] = ((CvSURFPoint*)cvGetSeqElem(imageKeypoints,ptpairs[i*2+1]))->pt;
+ }
+
+ _pt1 = cvMat(1, n, CV_32FC2, &pt1[0] );
+ _pt2 = cvMat(1, n, CV_32FC2, &pt2[0] );
+ if( !cvFindHomography( &_pt1, &_pt2, &_h, CV_RANSAC, 5 ))
+ return 0;
+
+ for( i = 0; i < 4; i++ )
+ {
+ double x = src_corners[i].x, y = src_corners[i].y;
+ double Z = 1./(h[6]*x + h[7]*y + h[8]);
+ double X = (h[0]*x + h[1]*y + h[2])*Z;
+ double Y = (h[3]*x + h[4]*y + h[5])*Z;
+ dst_corners[i] = cvPoint(cvRound(X), cvRound(Y));
+ }
+
+ return 1;
+}
+
+int main(int argc, char** argv)
+{
+ const char* object_filename = argc == 3 ? argv[1] : "box.png";
+ const char* scene_filename = argc == 3 ? argv[2] : "box_in_scene.png";
+
+ help();
+
+ IplImage* object = cvLoadImage( object_filename, CV_LOAD_IMAGE_GRAYSCALE );
+ IplImage* image = cvLoadImage( scene_filename, CV_LOAD_IMAGE_GRAYSCALE );
+ if( !object || !image )
+ {
+ fprintf( stderr, "Can not load %s and/or %s\n",
+ object_filename, scene_filename );
+ exit(-1);
+ }
+
+ CvMemStorage* storage = cvCreateMemStorage(0);
+
+ cvNamedWindow("Object", 1);
+ cvNamedWindow("Object Correspond", 1);
+
+ static CvScalar colors[] =
+ {
+ {{0,0,255}},
+ {{0,128,255}},
+ {{0,255,255}},
+ {{0,255,0}},
+ {{255,128,0}},
+ {{255,255,0}},
+ {{255,0,0}},
+ {{255,0,255}},
+ {{255,255,255}}
+ };
+
+ IplImage* object_color = cvCreateImage(cvGetSize(object), 8, 3);
+ cvCvtColor( object, object_color, CV_GRAY2BGR );
+
+ CvSeq* objectKeypoints = 0, *objectDescriptors = 0;
+ CvSeq* imageKeypoints = 0, *imageDescriptors = 0;
+ int i;
+ CvSURFParams params = cvSURFParams(500, 1);
+
+ double tt = (double)cvGetTickCount();
+ cvExtractSURF( object, 0, &objectKeypoints, &objectDescriptors, storage, params );
+ printf("Object Descriptors: %d\n", objectDescriptors->total);
+
+ cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params );
+ printf("Image Descriptors: %d\n", imageDescriptors->total);
+ tt = (double)cvGetTickCount() - tt;
+
+ printf( "Extraction time = %gms\n", tt/(cvGetTickFrequency()*1000.));
+
+ CvPoint src_corners[4] = {{0,0}, {object->width,0}, {object->width, object->height}, {0, object->height}};
+ CvPoint dst_corners[4];
+ IplImage* correspond = cvCreateImage( cvSize(image->width, object->height+image->height), 8, 1 );
+ cvSetImageROI( correspond, cvRect( 0, 0, object->width, object->height ) );
+ cvCopy( object, correspond );
+ cvSetImageROI( correspond, cvRect( 0, object->height, correspond->width, correspond->height ) );
+ cvCopy( image, correspond );
+ cvResetImageROI( correspond );
+
+#ifdef USE_FLANN
+ printf("Using approximate nearest neighbor search\n");
+#endif
+
+ if( locatePlanarObject( objectKeypoints, objectDescriptors, imageKeypoints,
+ imageDescriptors, src_corners, dst_corners ))
+ {
+ for( i = 0; i < 4; i++ )
+ {
+ CvPoint r1 = dst_corners[i%4];
+ CvPoint r2 = dst_corners[(i+1)%4];
+ cvLine( correspond, cvPoint(r1.x, r1.y+object->height ),
+ cvPoint(r2.x, r2.y+object->height ), colors[8] );
+ }
+ }
+ vector<int> ptpairs;
+#ifdef USE_FLANN
+ flannFindPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
+#else
+ findPairs( objectKeypoints, objectDescriptors, imageKeypoints, imageDescriptors, ptpairs );
+#endif
+ for( i = 0; i < (int)ptpairs.size(); i += 2 )
+ {
+ CvSURFPoint* r1 = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, ptpairs[i] );
+ CvSURFPoint* r2 = (CvSURFPoint*)cvGetSeqElem( imageKeypoints, ptpairs[i+1] );
+ cvLine( correspond, cvPointFrom32f(r1->pt),
+ cvPoint(cvRound(r2->pt.x), cvRound(r2->pt.y+object->height)), colors[8] );
+ }
+
+ cvShowImage( "Object Correspond", correspond );
+ for( i = 0; i < objectKeypoints->total; i++ )
+ {
+ CvSURFPoint* r = (CvSURFPoint*)cvGetSeqElem( objectKeypoints, i );
+ CvPoint center;
+ int radius;
+ center.x = cvRound(r->pt.x);
+ center.y = cvRound(r->pt.y);
+ radius = cvRound(r->size*1.2/9.*2);
+ cvCircle( object_color, center, radius, colors[0], 1, 8, 0 );
+ }
+ cvShowImage( "Object", object_color );
+
+ cvWaitKey(0);
+
+ cvDestroyWindow("Object");
+ cvDestroyWindow("Object Correspond");
+
+ return 0;
+}
View
18 VisualCortex/ObjectRecogntion/make
@@ -0,0 +1,18 @@
+#!/bin/sh
+
+ g++ -ggdb `pkg-config --cflags opencv` -o find_obj "find_obj.cpp" `pkg-config --libs opencv`;
+
+#if [ $# -gt 0 ] ; then
+# base=`basename $1 .c`
+# echo "compiling $base"
+# gcc -ggdb `pkg-config opencv --cflags --libs` $base.c -o $base
+#else
+# for i in *.c; do
+# echo "compiling $i"
+# gcc -ggdb `pkg-config --cflags opencv` -o `basename $i .c` $i `pkg-config --libs opencv`;
+# done
+# for i in *.cpp; do
+# echo "compiling $i"
+# g++ -ggdb `pkg-config --cflags opencv` -o `basename $i .cpp` $i `pkg-config --libs opencv`;
+# done
+#fi

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