public WrapFusedKltTracker(
InterestPointDetector<I> detector, PyramidKltForCombined<I, D> tracker, Class<I> imageType) {
this.detector = detector;
this.tracker = tracker;
derivType = GImageDerivativeOps.getDerivativeType(imageType);
gradient = FactoryDerivative.sobel(imageType, derivType);
int pyramidScaling[] = tracker.pyramidScaling;
pyramid = FactoryPyramid.discreteGaussian(pyramidScaling, -1, 2, true, imageType);
}
/**
* Any arbitrary implementation of InterestPointDetector, OrientationImage, DescribeRegionPoint
* can be combined into DetectDescribePoint. The syntax is more complex, but the end result is
* more flexible. This should only be done if there isn't a pre-made DetectDescribePoint.
*/
public static <T extends ImageSingleBand, D extends TupleDesc>
DetectDescribePoint<T, D> createFromComponents(Class<T> imageType) {
// create a corner detector
Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
GeneralFeatureDetector corner =
FactoryDetectPoint.createShiTomasi(new ConfigGeneralDetector(1000, 5, 1), false, derivType);
InterestPointDetector detector =
FactoryInterestPoint.wrapPoint(corner, 1, imageType, derivType);
// describe points using BRIEF
DescribeRegionPoint describe =
FactoryDescribeRegionPoint.brief(new ConfigBrief(true), imageType);
// Combine together.
// NOTE: orientation will not be estimated
return FactoryDetectDescribe.fuseTogether(detector, null, describe);
}
public static void main(String args[]) {
Class imageType = ImageFloat32.class;
Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
VisualizeAssociationMatchesApp app = new VisualizeAssociationMatchesApp(imageType, derivType);
List<PathLabel> inputs = new ArrayList<PathLabel>();
inputs.add(
new PathLabel(
"Cave",
"../data/evaluation/stitch/cave_01.jpg",
"../data/evaluation/stitch/cave_02.jpg"));
inputs.add(
new PathLabel(
"Kayak",
"../data/evaluation/stitch/kayak_02.jpg",
"../data/evaluation/stitch/kayak_03.jpg"));
inputs.add(
new PathLabel(
"Forest",
"../data/evaluation/scale/rainforest_01.jpg",
"../data/evaluation/scale/rainforest_02.jpg"));
inputs.add(
new PathLabel(
"Building",
"../data/evaluation/stitch/apartment_building_01.jpg",
"../data/evaluation/stitch/apartment_building_02.jpg"));
inputs.add(
new PathLabel(
"Trees Rotate",
"../data/evaluation/stitch/trees_rotate_01.jpg",
"../data/evaluation/stitch/trees_rotate_03.jpg"));
app.setPreferredSize(new Dimension(1000, 500));
app.setSize(1000, 500);
app.setInputList(inputs);
// wait for it to process one image so that the size isn't all screwed up
while (!app.getHasProcessedImage()) {
Thread.yield();
}
ShowImages.showWindow(app, "Associated Features");
}
public IntensityFeatureScaleSpacePyramidApp(Class<T> imageType, Class<D> derivType) {
super(1);
this.imageType = imageType;
addAlgorithm(
0,
"Hessian Det",
new WrapperHessianBlobIntensity<T, D>(HessianBlobIntensity.Type.DETERMINANT, derivType));
addAlgorithm(
0,
"Laplacian",
new WrapperHessianBlobIntensity<T, D>(HessianBlobIntensity.Type.TRACE, derivType));
addAlgorithm(
0,
"Harris",
new WrapperGradientCornerIntensity<T, D>(
FactoryIntensityPointAlg.harris(2, 0.4f, false, derivType)));
addAlgorithm(
0,
"Shi Tomasi",
new WrapperGradientCornerIntensity<T, D>(
FactoryIntensityPointAlg.shiTomasi(2, false, derivType)));
addAlgorithm(
0,
"FAST 12",
new WrapperFastCornerIntensity<T, D>(FactoryIntensityPointAlg.fast12(5, 11, imageType)));
addAlgorithm(0, "KitRos", new WrapperKitRosCornerIntensity<T, D>(derivType));
addAlgorithm(
0,
"Median",
new WrapperMedianCornerIntensity<T, D>(FactoryBlurFilter.median(imageType, 2), imageType));
setMainGUI(gui);
double scales[] = new double[25];
for (int i = 0; i < scales.length; i++) {
scales[i] = Math.exp(i * 0.15);
}
pyramid = new ScaleSpacePyramid<T>(imageType, scales);
anyDerivative =
GImageDerivativeOps.createDerivatives(imageType, FactoryImageGenerator.create(derivType));
}
