Exemple #1
0
bool TrackerSamplerCS::samplingImpl( const Mat& image, Rect boundingBox, std::vector<Mat>& sample )
{

  trackedPatch = boundingBox;
  Size imageSize( image.cols, image.rows );
  validROI = Rect( 0, 0, imageSize.width, imageSize.height );

  Size trackedPatchSize( trackedPatch.width, trackedPatch.height );
  Rect trackingROI = getTrackingROI( params.searchFactor );

  sample = patchesRegularScan( image, trackingROI, trackedPatchSize );

  return true;
}
Exemple #2
0
void track3(ImageSource::InputDevice input, int numBaseClassifier, float overlap, float searchFactor, char* resultDir, Rect initBB, char* source = NULL)
{
	unsigned char *curFrame=NULL;
        int key;
	//choose the image source
	ImageSource *imageSequenceSource;
	switch (input)
	{
	case ImageSource::AVI:
		imageSequenceSource = new ImageSourceAVIFile(source);
		break;
	case ImageSource::DIRECTORY:
		imageSequenceSource = new ImageSourceDir(source);
		break;
	case ImageSource::USB:
		imageSequenceSource = new ImageSourceUSBCam();
		break;
	default:
		return;
	}

	ImageHandler* imageSequence = new ImageHandler (imageSequenceSource);
	imageSequence->getImage();

	imageSequence->viewImage ("Tracking...", false);

		trackingRect=initBB;


	curFrame = imageSequence->getGrayImage ();
	ImageRepresentation* curFrameRep = new ImageRepresentation(curFrame, imageSequence->getImageSize());
	Rect wholeImage;
	wholeImage = imageSequence->getImageSize();


        // Pula o inicio do video
        for(int t = 0; t < 60; t++, imageSequence->getImage());


        IplImage *image;
        image = imageSequence->getIplImage();


//cvWaitKey(0);


        printf ("init tracker...");
        Classifier* tracker;
        tracker = new Classifier(image, trackingRect);
        printf (" done.\n");

	Size trackingRectSize;
	trackingRectSize = trackingRect;
	printf ("start tracking (stop by pressing any key)...\n\n");

// Inicializa o detector
Detector* detector;
detector = new Detector(tracker->getClassifier());
Rect trackedPatch = trackingRect;
Rect validROI;
validROI.upper = validROI.left = 0;
validROI.height = image->height;
validROI.width = image->width;


	key=(char)-1;
        while (key==(char)-1)
	{





		imageSequence->getImage();
                image = imageSequence->getIplImage();




curFrame = imageSequence->getGrayImage ();
if (curFrame == NULL) break;

//calculate the patches within the search region
Patches *trackingPatches;
Rect searchRegion;
searchRegion = getTrackingROI(searchFactor, trackedPatch, validROI);
trackingPatches = new PatchesRegularScan(searchRegion, wholeImage, trackingRectSize, overlap);

curFrameRep->setNewImageAndROI(curFrame, searchRegion);

detector->classifySmooth(curFrameRep, trackingPatches);

trackedPatch = trackingPatches->getRect(detector->getPatchIdxOfBestDetection());

if (detector->getNumDetections() <= 0){printf("Lost...\n");break;}



                // Treina o classificador
                tracker->train(image,trackedPatch);


float alpha, confidence, eval;

alpha = tracker->getSumAlphaClassifier();
confidence = detector->getConfidenceOfBestDetection() / alpha;
eval = tracker->classify(image, trackedPatch);

printf("alpha: %5.3f confidence: %5.3f evalOficial: %5.3f ", alpha, confidence, eval);

int orig = trackedPatch.upper;
trackedPatch.upper -= 5;
for(int i = 0; i < 10; i++){
    eval = tracker->classify(image, trackedPatch);
    printf("%5.3f ", eval);
    trackedPatch.upper += 1;
    imageSequence->paintRectangle (trackedPatch, Color (0,255,0), 1);
}
trackedPatch.upper = orig;

printf("\n");




		//display results
                imageSequence->paintRectangle (trackedPatch, Color (255,0,0), 5);
		imageSequence->viewImage ("Tracking...", false);
		key=cvWaitKey(200);
	}

	//clean up
	delete tracker;
	delete imageSequenceSource;
	delete imageSequence;
	if (curFrame == NULL)
		delete[] curFrame;
	delete curFrameRep;
}