diff --git a/Comparison/src/main/java/cz/fidentis/analyst/icp/IcpTransformer.java b/Comparison/src/main/java/cz/fidentis/analyst/icp/IcpTransformer.java
index 022861ed796af59bdf5d128b0b3d823f846c6178..da76e5a2cfba20e2c22a7dd38df46888db0cf865 100644
--- a/Comparison/src/main/java/cz/fidentis/analyst/icp/IcpTransformer.java
+++ b/Comparison/src/main/java/cz/fidentis/analyst/icp/IcpTransformer.java
@@ -9,6 +9,7 @@ import cz.fidentis.analyst.mesh.core.MeshPoint;
import cz.fidentis.analyst.visitors.mesh.HausdorffDistance;
import cz.fidentis.analyst.visitors.mesh.sampling.NoSampling;
import cz.fidentis.analyst.visitors.mesh.sampling.PointSampling;
+import cz.fidentis.analyst.visitors.mesh.sampling.RandomSampling;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
@@ -81,6 +82,29 @@ public class IcpTransformer extends MeshVisitor {
private final PointSampling samplingStrategy;
+ /**
+ * Constructor for random sampling, which is the best performing downsampling strategy.
+ *
+ * @param mainFacet Primary mesh facet. Must not be {@code null}.
+ * Inspected facets are transformed toward this primary mesh.
+ * @param maxIteration Maximal number of ICP iterations (it includes computing
+ * new transformation and applying it). A number bigger than zero.
+ * Reasonable number seems to be 10.
+ * @param scale If {@code true}, then the scale factor is also computed.
+ * @param error Acceptable error - a number bigger than or equal to zero.
+ * Mean distance of vertices is computed for each ICP iteration.
+ * If the difference between the previous and current mean distances is less than the error,
+ * then the ICP computation stops. Reasonable number seems to be 0.05.
+ * @param numSamples Number of samples for downsampling. Use 1000 for best performance. Zero = no downsampling
+ * @throws IllegalArgumentException if some parameter is wrong
+ */
+ public IcpTransformer(MeshFacet mainFacet, int maxIteration, boolean scale, double error, int numSamples) {
+ this(new HashSet<>(Collections.singleton(mainFacet)), maxIteration, scale, error, (numSamples == 0) ? new NoSampling() : new RandomSampling(numSamples));
+ if (mainFacet == null) {
+ throw new IllegalArgumentException("mainFacet");
+ }
+ }
+
/**
* Constructor.
*
@@ -90,8 +114,10 @@ public class IcpTransformer extends MeshVisitor {
* new transformation and applying it). A number bigger than zero.
* Reasonable number seems to be 10.
* @param scale If {@code true}, then the scale factor is also computed.
- * @param error Acceptable error. A number bigger than or equal to zero.
- * When reached, then the ICP stops. Reasonable number seems to be 0.05.
+ * @param error Acceptable error - a number bigger than or equal to zero.
+ * Mean distance of vertices is computed for each ICP iteration.
+ * If the difference between the previous and current mean distances is less than the error,
+ * then the ICP computation stops. Reasonable number seems to be 0.05.
* @param strategy One of the reduction strategies. If {@code null}, then {@link NoUndersampling} is used.
* @throws IllegalArgumentException if some parameter is wrong
*/
@@ -111,8 +137,10 @@ public class IcpTransformer extends MeshVisitor {
* new transformation and applying it). A number bigger than zero.
* Reasonable number seems to be 10.
* @param scale If {@code true}, then the scale factor is also computed.
- * @param error Acceptable error. A number bugger than or equal to zero.
- * When reached, then the ICP stops. Reasonable number seems to be 0.05.
+ * @param error Acceptable error - a number bigger than or equal to zero.
+ * Mean distance of vertices is computed for each ICP iteration.
+ * If the difference between the previous and current mean distances is less than the error,
+ * then the ICP computation stops. Reasonable number seems to be 0.05.
* @param strategy One of the reduction strategies. If {@code null}, then {@link NoUndersampling} is used.
* @throws IllegalArgumentException if some parameter is wrong
*/
@@ -142,8 +170,10 @@ public class IcpTransformer extends MeshVisitor {
* new transformation and applying it). A number bigger than zero.
* Reasonable number seems to be 10.
* @param scale If {@code true}, then the scale factor is also computed.
- * @param error Acceptable error. A number bugger than or equal to zero.
- * When reached, then the ICP stops. Reasonable number seems to be 0.05.
+ * @param error Acceptable error - a number bigger than or equal to zero.
+ * Mean distance of vertices is computed for each ICP iteration.
+ * If the difference between the previous and current mean distances is less than the error,
+ * then the ICP computation stops. Reasonable number seems to be 0.05.
* @param strategy One of the reduction strategies. If {@code null}, then {@link NoUndersampling} is used.
* @throws IllegalArgumentException if some parameter is wrong
*/
@@ -163,7 +193,10 @@ public class IcpTransformer extends MeshVisitor {
* new transformation and applying it). A number bigger than zero.
* Reasonable number seems to be 10.
* @param scale If {@code true}, then the scale factor is also computed.
- * @param error Acceptable error. A number bugger than or equal to zero. When reached, then the ICP stops.
+ * @param error Acceptable error - a number bigger than or equal to zero.
+ * Mean distance of vertices is computed for each ICP iteration.
+ * If the difference between the previous and current mean distances is less than the error,
+ * then the ICP computation stops. Reasonable number seems to be 0.05.
* @param strategy One of the reduction strategies. If {@code null}, then {@link NoUndersampling} is used.
* @throws IllegalArgumentException if some parameter is wrong
*/
@@ -259,6 +292,8 @@ public class IcpTransformer extends MeshVisitor {
false // auto crop
);
+ //int numSamples = samplingStrategy.getNumDownsampledPoints(transformedFacet.getNumberOfVertices());
+ //samplingStrategy.setRequiredSamples(200);
MeshFacet reducedFacet = new UndersampledMeshFacet(transformedFacet, samplingStrategy);
int currentIteration = 0;
@@ -289,7 +324,12 @@ public class IcpTransformer extends MeshVisitor {
applyTransformation(reducedFacet, transformation);
}
- currentIteration ++;
+ currentIteration++;
+
+ //if (currentIteration >= 3) {
+ // samplingStrategy.setRequiredSamples(numSamples);
+ // reducedFacet = new UndersampledMeshFacet(transformedFacet, samplingStrategy);
+ //}
}
}
diff --git a/Comparison/src/main/java/cz/fidentis/analyst/visitors/mesh/sampling/PointSampling.java b/Comparison/src/main/java/cz/fidentis/analyst/visitors/mesh/sampling/PointSampling.java
index 12202b757e2b2eef05e13e772aa2eaa94a28a89d..5890d1fd81af6a3dcaa5320580a62c1648f38eea 100644
--- a/Comparison/src/main/java/cz/fidentis/analyst/visitors/mesh/sampling/PointSampling.java
+++ b/Comparison/src/main/java/cz/fidentis/analyst/visitors/mesh/sampling/PointSampling.java
@@ -134,7 +134,7 @@ public abstract class PointSampling extends MeshVisitor {
* @param origPoints Original number of vertices
* @return number of points to be returned after downsampling.
*/
- protected int getNumDownsampledPoints(int origPoints) {
+ public int getNumDownsampledPoints(int origPoints) {
switch (this.samplingType) {
case PERCENTAGE:
return (int) (origPoints * this.samplingLimit);
diff --git a/GUI/src/main/java/cz/fidentis/analyst/batch/BatchPanel.java b/GUI/src/main/java/cz/fidentis/analyst/batch/BatchPanel.java
index be2eaeb35119355b61a7672e6378c8a53a642fd5..8b6ea4c9fe008329b5c0dbdc99c0a9f6ad88fc45 100644
--- a/GUI/src/main/java/cz/fidentis/analyst/batch/BatchPanel.java
+++ b/GUI/src/main/java/cz/fidentis/analyst/batch/BatchPanel.java
@@ -66,7 +66,7 @@ public class BatchPanel extends ControlPanel {
jButton1.addActionListener(createListener(action, ACTION_COMMAND_COMPUTE_ICP));
- spinSlider1.initInteger(2000, 0, 5000, 1);
+ spinSlider1.initInteger(1000, 0, 5000, 1); // downsampling strength
jComboBox2.addItem(SIMILARITY_APPROX_HD);
jComboBox2.addItem(SIMILARITY_COMPLETE_HD);
diff --git a/GUI/src/main/java/cz/fidentis/analyst/batch/IcpTask.java b/GUI/src/main/java/cz/fidentis/analyst/batch/IcpTask.java
index 67d6cf51a44497be34a84d5e271cee51043c6fb9..886e86471b9989c3c03565a833233f4f825cce9d 100644
--- a/GUI/src/main/java/cz/fidentis/analyst/batch/IcpTask.java
+++ b/GUI/src/main/java/cz/fidentis/analyst/batch/IcpTask.java
@@ -27,6 +27,9 @@ import javax.swing.SwingWorker;
* @author Radek Oslejsek
*/
public class IcpTask extends SwingWorker<MeshModel, HumanFace> {
+
+ private static final double ICP_ERROR = 0.3; //0.05;
+ private static final int ICP_ITERS = 100;
private HumanFace avgFace;
private final ProgressDialog progressDialog;
@@ -121,14 +124,14 @@ public class IcpTask extends SwingWorker<MeshModel, HumanFace> {
HumanFaceUtils.alignMeshes(
initFace,
face, // is transformed
- 100, // max iterations
+ ICP_ITERS, // max iterations
controlPanel.scaleIcp(),
- 0.3, // error
+ ICP_ERROR, // error
sampling,
false // drop k-d tree, if exists
);
icpComputationTime.stop();
- System.out.println(sampling);
+ //System.out.println(sampling);
}
if (computeAvgFace) { // AVG template face
diff --git a/GUI/src/main/java/cz/fidentis/analyst/tests/IcpDownsampling.java b/GUI/src/main/java/cz/fidentis/analyst/tests/IcpDownsampling.java
index 216a461cc2b1fd2914156fc8a882f2c631bcb1f8..2df712c7c4643955b4197f60c31b55d97d5d21bf 100644
--- a/GUI/src/main/java/cz/fidentis/analyst/tests/IcpDownsampling.java
+++ b/GUI/src/main/java/cz/fidentis/analyst/tests/IcpDownsampling.java
@@ -3,10 +3,9 @@ package cz.fidentis.analyst.tests;
import cz.fidentis.analyst.batch.Stopwatch;
import cz.fidentis.analyst.face.HumanFace;
import cz.fidentis.analyst.face.HumanFaceUtils;
+import cz.fidentis.analyst.icp.UndersampledMeshFacet;
+import cz.fidentis.analyst.mesh.core.MeshFacet;
import cz.fidentis.analyst.mesh.core.MeshModel;
-import cz.fidentis.analyst.symmetry.Plane;
-import cz.fidentis.analyst.symmetry.SymmetryEstimator;
-import cz.fidentis.analyst.symmetry.SymmetryEstimatorRobust;
import cz.fidentis.analyst.visitors.mesh.HausdorffDistance;
import cz.fidentis.analyst.visitors.mesh.sampling.CurvatureSampling;
import cz.fidentis.analyst.visitors.mesh.sampling.NoSampling;
@@ -19,6 +18,7 @@ import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.ArrayList;
+import java.util.Collections;
import java.util.List;
import java.util.Map;
import java.util.SortedMap;
@@ -48,13 +48,13 @@ public class IcpDownsampling {
.limit(MAX_SAMPLES)
.collect(Collectors.toList());
- SortedMap<Integer, Stopwatch> efficiency = new TreeMap<>();
- SortedMap<Integer, List<Double>> precision = new TreeMap<>();
+ SortedMap<Integer, Stopwatch> efficiency = new TreeMap<>(Collections.reverseOrder());
+ SortedMap<Integer, List<Double>> precision = new TreeMap<>(Collections.reverseOrder());
- //String alg = "random";
+ String alg = "random";
//String alg = "gaussian";
//String alg = "uniform space";
- String alg = "uniform mesh";
+ //String alg = "uniform mesh";
int counter = 1;
for (int i = 0; i < faces.size(); i += 5) {
@@ -78,7 +78,7 @@ public class IcpDownsampling {
});
System.out.println();
System.out.println("Avg. Precision - " + sampling + " sampling:");
- System.out.println("# samples;average similarity;variance");
+ System.out.println("# samples;dissimilarity;variance");
precision.entrySet().forEach(e -> {
double avg = e.getValue().stream()
.mapToDouble(val -> val)
@@ -100,64 +100,86 @@ public class IcpDownsampling {
//double[] percs = new double[]{0.5,1,2,4,6,8,10,15,20,30,40,50,60,70,80,85,90,92,94,96,98,100};
//double[] percs = new double[]{100,90,80,70,60,50,40,30,20,15,10,8,6,4,2,1,0.5};
//int[] samples = new int[]{0,200,500,1000,2000,3000,5000,10000,20000,30000,40000};
- int[] samples = new int[]{0,200,500,1000,2000,3000,5000};
+ //int[] samples = new int[]{0,200,500,1000,2000,3000,5000};
+ //int[] samples = new int[]{50,100,150,300,400};
+ //int[] samples = new int[]{0,50,100,150,200,300,400,500,1000,2000,3000,5000,10000,20000,30000};
+ //int[] samples = new int[]{5,10,20,30,40,50};
+ int[] samples = new int[]{0,40,50,100,150,200,300,400,500,1000,2000,3000,5000,10000,20000,30000};
HumanFace priFace = new HumanFace(priFacePath.toFile());
priFace.computeKdTree(false);
- SymmetryEstimator seVisitor = new SymmetryEstimatorRobust(new UniformSpaceSampling(), 100, 1000);
- priFace.getMeshModel().compute(seVisitor);
- priFace.setSymmetryPlane(seVisitor.getSymmetryPlane());
HumanFace secFaceFromFile = new HumanFace(secFacePath.toFile());
- seVisitor = new SymmetryEstimatorRobust(new UniformSpaceSampling(), 100, 1000);
- secFaceFromFile.getMeshModel().compute(seVisitor);
- secFaceFromFile.setSymmetryPlane(seVisitor.getSymmetryPlane());
-
System.out.println(secFaceFromFile.getShortName());
for (int i: samples) {
HumanFace secFace = new HumanFace(new MeshModel(secFaceFromFile.getMeshModel()), secFaceFromFile.getId());
- secFace.setSymmetryPlane(new Plane(secFaceFromFile.getSymmetryPlane()));
- PointSampling sampling;
+ PointSampling secSampling;
+ PointSampling priSampling;
switch (samp) {
case "random":
- sampling = new RandomSampling();
+ secSampling = new RandomSampling();
+ priSampling = new RandomSampling();
break;
case "gaussian":
- sampling = new CurvatureSampling(CurvatureSampling.CurvatureAlg.GAUSSIAN);
+ secSampling = new CurvatureSampling(CurvatureSampling.CurvatureAlg.GAUSSIAN);
+ priSampling = new CurvatureSampling(CurvatureSampling.CurvatureAlg.GAUSSIAN);
break;
case "uniform space":
- sampling = new UniformSpaceSampling();
+ secSampling = new UniformSpaceSampling();
+ priSampling = new UniformSpaceSampling();
break;
case "uniform mesh":
- sampling = new UniformSurfaceSampling();
+ secSampling = new UniformSurfaceSampling();
+ priSampling = new UniformSurfaceSampling();
break;
default:
return;
}
+ /*
+ if (samples[i] == 0) {
+ secSampling = new NoSampling();
+ priSampling = new NoSampling();
+ } else {
+ secSampling.setRequiredSamples(i);
+ priSampling.setRequiredSamples(i);
+ }
+ */
+
if (i == 0) {
- sampling = new NoSampling();
+ priSampling = new NoSampling();
} else {
- //sampling.setRequiredSamples(i/100.0);
- sampling.setRequiredSamples(i);
+ priSampling.setRequiredSamples(i);
}
+ secSampling.setRequiredSamples(5000);
efficiency.computeIfAbsent(i, k-> new Stopwatch("")).start();
- HumanFaceUtils.alignSymmetryPlanes(priFace, secFace, false, true);
- HumanFaceUtils.alignMeshes(
+ HumanFaceUtils.alignMeshes(
+ downsamplePriFace(priFace, priSampling),
+ secFace, // is transformed
+ 100, // max iterations
+ false,// scale
+ 0.05, // error
+ secSampling,
+ false // drop k-d tree of the secFace, if exists
+ );
+ /*
+ HumanFaceUtils.alignMeshes( /// ORIG SETTING
priFace,
secFace, // is transformed
100, // max iterations
false,// scale
- 0.3, // error
- sampling,
- false // drop k-d tree, if exists
+ 0.05, // error
+ secSampling,
+ false // drop k-d tree of the secFace, if exists
);
+ */
efficiency.get(i).stop();
- System.out.println("" + sampling);
+ System.out.println(" Primary face: " + priSampling);
+ System.out.println("Secondary face: " + secSampling);
HausdorffDistance hd = new HausdorffDistance(
priFace.getKdTree(),
@@ -171,4 +193,12 @@ public class IcpDownsampling {
}
System.out.println();
}
+
+ private static HumanFace downsamplePriFace(HumanFace priFace, PointSampling sampling) {
+ MeshFacet reducedFacet = new UndersampledMeshFacet(priFace.getMeshModel().getFacets().get(0), sampling);
+ MeshModel model = new MeshModel();
+ model.setFacets(List.of(reducedFacet));
+ HumanFace ret = new HumanFace(model, priFace.getId());
+ return ret;
+ }
}