diff --git a/Comparison/src/main/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritized.java b/Comparison/src/main/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritized.java
index 0d92bdce167e5f611a9f2b37b6860c648c91bac5..83ed7f1c7ce671694f97e4f66067e24cefe4d2b8 100644
--- a/Comparison/src/main/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritized.java
+++ b/Comparison/src/main/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritized.java
@@ -16,6 +16,7 @@ import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
+import java.util.stream.IntStream;
import javax.vecmath.Point3d;
/**
@@ -28,7 +29,7 @@ import javax.vecmath.Point3d;
* points separately</li>
* <li>Priorities of the faces' vertices with respect to all the given types
* of feature points merged together</li>
- * <li>Weighted Hausdorff distance with respect to the given types of feature
+ * <li>Average weighted Hausdorff distance with respect to the given types of feature
* points for each of the faces' mesh facets</li>
* </ul>
* This visitor is instantiated with a single k-d tree (either given as the input
@@ -220,21 +221,24 @@ public class HausdorffDistancePrioritized extends HumanFaceVisitor {
}
/**
- * For all visited faces' mesh facets, the method returns the weighted Hausdorff distance
- * (total sum of weighted distances of all mesh facet's vertices to the source facets).
- * The weighted distances are calculated with respect to the given types of
- * feature points - for each feature point type separately.
+ * For all visited faces' mesh facets, the method returns the average weighted Hausdorff distance
+ * with respect to the given types of feature points (i.e. the sum of weighted distances
+ * of the mesh facet's vertices to the source facets divided by the number of vertices
+ * located within the feature point's priority sphere).
+ * The average weighted distances are calculated for each type of feature point separately.
*
* Keys in the map contain human faces whose mesh facets were measured with the
* source facets.
* For each human face, there is a map of examined types of feature points.
* Each feature point type then stores a map of the face's mesh facets together with
- * the total sums of weighted distances of all their vertices to the source facets.
- * The weighted distances are calculated with respect to the face's feature point
+ * the average weighted distances of their vertices to the source facets.
+ * The average weighted distances are calculated with respect to the face's feature point
* of the corresponding type.
+ * <i>If there is no vertex within the priority sphere of a feature point,
+ * the value of the average weighted Hausdorff distance is {@link Double#NaN}</i>
*
- * @return Weighted Hausdorff distances with respect to the given types
- * of feature points for each of the visited faces' mesh facets
+ * @return Average weighted Hausdorff distances with respect to the given types
+ * of feature points
*/
public Map<HumanFace, Map<FeaturePointType, Map<MeshFacet, Double>>> getFeaturePointWeights() {
return Collections.unmodifiableMap(featurePointWeights);
@@ -302,6 +306,8 @@ public class HausdorffDistancePrioritized extends HumanFaceVisitor {
// Compute the Hasudorff distance using the 'distanceVisitor'
humanFace.getMeshModel().compute(distanceVisitor, inParallel());
+ final Map<MeshFacet, List<Double>> hausdorffDistances = distanceVisitor.getDistances();
+
// Compute priorities of humanFace's vertices for each of the given feature point types
for (final FeaturePointType fpType: featurePointTypes) {
final FeaturePoint featurePoint = humanFace.getFeaturePoints().get(fpType.getType()); // Get feature point of desired type
@@ -313,24 +319,28 @@ public class HausdorffDistancePrioritized extends HumanFaceVisitor {
priorities.computeIfAbsent(humanFace, face -> new HashMap<>())
.computeIfAbsent(fpType, featurePointType -> new HashMap<>())
.putAll(priorityVisitor.getPriorities());
-
- // TODO implement featurePointWeights correctly!!
- // DO NOT measure distance to feature point
- // DO measure distance to source facets
- featurePointWeights.computeIfAbsent(humanFace, face -> new HashMap<>())
- .computeIfAbsent(fpType, featurePointType -> new HashMap<>())
- .putAll(priorityVisitor.getWeightedDistances());
}
- /*
- * Merge priorities computed for the current feature point type with
- * the priorities of already computed feature point types.
- */
for (final Map.Entry<MeshFacet, List<Double>> entry: priorityVisitor.getPriorities().entrySet()) {
final MeshFacet facet = entry.getKey();
final List<Double> facetPriorities = entry.getValue();
synchronized (this) {
+ /*
+ * Calculate the average weighted Hausdorff distance for the feature point.
+ */
+ final List<Double> facetDistances = hausdorffDistances.get(facet);
+ featurePointWeights.computeIfAbsent(humanFace, face -> new HashMap<>())
+ .computeIfAbsent(fpType, featurePointType -> new HashMap<>())
+ .put(facet, IntStream.range(0, facetDistances.size())
+ .filter(i -> facetPriorities.get(i) > 0) // Filter out vertices that are outside of the priority sphere
+ .mapToDouble(i -> facetDistances.get(i) * facetPriorities.get(i))
+ .average()
+ .orElse(Double.NaN)); // If there is no vertex in the priority sphere
+
+ /*
+ * Merge priorities computed for the current feature point type with the priorities of already computed feature point types.
+ */
final List<Double> storedFacetPriorities = mergedPriorities
.computeIfAbsent(humanFace, face -> new HashMap<>())
.get(facet);
diff --git a/Comparison/src/test/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritizedTest.java b/Comparison/src/test/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritizedTest.java
index f70629900d09dfb9c5c5a843fd763416b9e20fd7..a7315155e3a19555cbc843478ef336863fab7ffa 100644
--- a/Comparison/src/test/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritizedTest.java
+++ b/Comparison/src/test/java/cz/fidentis/analyst/visitors/face/HausdorffDistancePrioritizedTest.java
@@ -18,6 +18,7 @@ import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
+import java.util.stream.Collectors;
import javax.vecmath.Point3d;
import javax.vecmath.Vector3d;
import static org.junit.jupiter.api.Assertions.assertEquals;
@@ -26,7 +27,7 @@ import org.junit.jupiter.api.Test;
public class HausdorffDistancePrioritizedTest {
- private static final double DELTA = 1e-11;
+ private static final double DELTA = 1e-15;
private final File boy = new File("src/test/resources/cz/fidentis/analyst/average_boy_17-20.obj");
@@ -40,8 +41,11 @@ public class HausdorffDistancePrioritizedTest {
private final MeshFacet facet6 = getTrivialFacet(VERTICES_NUM, 0, 0, -0.1, 0);
private final List<MeshFacet> facets = List.of(facet1, facet2, facet3, facet4, facet5, facet6);
+ private final List<MeshFacet> facets2 = List.of(getTrivialFacet(1, 0, 0, 0, 0));
+
private final List<Double> prioritiesListFP1 = List.of(1d, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, 0.1, 0d, 0d);
private final double weightedDistanceFP1 = 0 + 0.09 + 0.16 + 0.21 + 0.24 + 0.25 + 0.24 + 0.21 + 0.16 + 0.09 + 0 + 0;
+ private final double averageWeightedDistanceFP1 = weightedDistanceFP1 / 10; // There are 10 vertices inside the priority sphere
private final Point3d featurePoint1 = new Point3d(0, 0, 0);
private final FeaturePointType fpType1 = new FeaturePointType(0, null, null, null);
@@ -51,13 +55,16 @@ public class HausdorffDistancePrioritizedTest {
facet4, prioritiesListFP1,
facet5, prioritiesListFP1,
facet6, prioritiesListFP1);
- private final Map<MeshFacet, Double> expectedWeightedDistancesMapFP1 = Map.of(facet1, weightedDistanceFP1,
- facet2, weightedDistanceFP1,
- facet3, weightedDistanceFP1,
- facet4, weightedDistanceFP1,
- facet5, weightedDistanceFP1,
- facet6, weightedDistanceFP1);
-
+ private final Map<MeshFacet, Double> expectedWeightedDistancesMapFP1 = Map.of(facet1, averageWeightedDistanceFP1,
+ facet2, averageWeightedDistanceFP1,
+ facet3, averageWeightedDistanceFP1,
+ facet4, averageWeightedDistanceFP1,
+ facet5, -averageWeightedDistanceFP1,
+ facet6, averageWeightedDistanceFP1);
+ private final Map<MeshFacet, Double> expectedAbsoluteWeightedDistancesMapFP1 = expectedWeightedDistancesMapFP1
+ .entrySet()
+ .stream()
+ .collect(Collectors.toMap(entry -> entry.getKey(), entry -> Math.abs(entry.getValue())));
private MeshFacet getTrivialFacet(int count, double xSpace, double ySpace, double zSpace, int offset) {
final MeshFacet facet = new MeshFacetImpl();
@@ -207,7 +214,11 @@ public class HausdorffDistancePrioritizedTest {
expectedMergedPrioritiesMap.put(facet, prioritiesListFP1);
}
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, true, false);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ true,
+ false);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}
@@ -229,9 +240,9 @@ public class HausdorffDistancePrioritizedTest {
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP2 = new HashMap<>();
for (final MeshFacet facet: facets) {
- expectedWeightedDistancesMapFP2.put(facet, 0d);
+ expectedWeightedDistancesMapFP2.put(facet, Double.NaN);
}
- final Map<FeaturePointType, Map<MeshFacet, Double>> expectedFeaturePointsWeights = Map.of(fpType1, expectedWeightedDistancesMapFP1,
+ final Map<FeaturePointType, Map<MeshFacet, Double>> expectedFeaturePointsWeights = Map.of(fpType1, expectedAbsoluteWeightedDistancesMapFP1,
fpType2, expectedWeightedDistancesMapFP2);
final Map<MeshFacet, List<Double>> expectedMergedPrioritiesMap = new HashMap<>();
@@ -239,7 +250,11 @@ public class HausdorffDistancePrioritizedTest {
expectedMergedPrioritiesMap.put(facet, prioritiesListFP1);
}
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, false, false);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ false,
+ false);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}
@@ -262,9 +277,9 @@ public class HausdorffDistancePrioritizedTest {
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP2 = new HashMap<>();
for (final MeshFacet facet: facets) {
- expectedWeightedDistancesMapFP2.put(facet, 0d);
+ expectedWeightedDistancesMapFP2.put(facet, Double.NaN);
}
- expectedWeightedDistancesMapFP2.put(facet1, 0 + 0.09 + 0.16 + 0.21 + 0.24 + 0.25 + 0.24 + 0.21 + 0.16 + 0.09 + 0 + 0.09);
+ expectedWeightedDistancesMapFP2.put(facet1, (0 + 0.01 + 0.04 + 0.09 + 0.16 + 0.25 + 0.36 + 0.49 + 0.64 + 0.81 + 1 + 0.99) / 11);
final Map<FeaturePointType, Map<MeshFacet, Double>> expectedFeaturePointsWeights = Map.of(fpType1, expectedWeightedDistancesMapFP1,
fpType2, expectedWeightedDistancesMapFP2);
@@ -274,7 +289,11 @@ public class HausdorffDistancePrioritizedTest {
}
expectedMergedPrioritiesMap.put(facet1, List.of(1d, 0.9, 0.8, 0.7, 0.6, 0.5, 0.6, 0.7, 0.8, 0.9, 1d, 0.9));
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, true, false);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ true,
+ false);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}
@@ -311,14 +330,14 @@ public class HausdorffDistancePrioritizedTest {
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP3 = new HashMap<>();
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP4 = new HashMap<>();
for (final MeshFacet facet: facets) {
- expectedWeightedDistancesMapFP2.put(facet, 0d);
- expectedWeightedDistancesMapFP3.put(facet, 0d);
- expectedWeightedDistancesMapFP4.put(facet, 0d);
+ expectedWeightedDistancesMapFP2.put(facet, Double.NaN);
+ expectedWeightedDistancesMapFP3.put(facet, Double.NaN);
+ expectedWeightedDistancesMapFP4.put(facet, Double.NaN);
}
- final double weightedDistance = 0 + 0.09 + 0.16 + 0.21 + 0.24 + 0.25 + 0.24 + 0.21 + 0.16 + 0.09 + 0 + 0.09;
+ final double weightedDistance = (0 + 0.01 + 0.04 + 0.09 + 0.16 + 0.25 + 0.36 + 0.49 + 0.64 + 0.81 + 1 + 0.99) / 11;
expectedWeightedDistancesMapFP2.put(facet1, weightedDistance);
expectedWeightedDistancesMapFP3.put(facet3, weightedDistance);
- expectedWeightedDistancesMapFP4.put(facet5, weightedDistance);
+ expectedWeightedDistancesMapFP4.put(facet5, -weightedDistance);
final Map<FeaturePointType, Map<MeshFacet, Double>> expectedFeaturePointsWeights = Map.of(fpType1, expectedWeightedDistancesMapFP1,
fpType2, expectedWeightedDistancesMapFP2,
fpType3, expectedWeightedDistancesMapFP3,
@@ -333,7 +352,11 @@ public class HausdorffDistancePrioritizedTest {
expectedMergedPrioritiesMap.put(facet3, mergedPriorities);
expectedMergedPrioritiesMap.put(facet5, mergedPriorities);
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, false, false);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ true,
+ false);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}
@@ -370,10 +393,10 @@ public class HausdorffDistancePrioritizedTest {
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP2 = new HashMap<>();
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP3 = new HashMap<>();
for (final MeshFacet facet: facets) {
- expectedWeightedDistancesMapFP2.put(facet, 0d);
- expectedWeightedDistancesMapFP3.put(facet, 0d);
+ expectedWeightedDistancesMapFP2.put(facet, Double.NaN);
+ expectedWeightedDistancesMapFP3.put(facet, Double.NaN);
}
- final double weightedDistance = 0d + 0d + 0d + 0d + 0d + 0d + 0d + 0d + 0d + 0d + vertexDistance * vertexPriority + 0d;
+ final double weightedDistance = 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 1 * vertexPriority + 0;
expectedWeightedDistancesMapFP2.put(facet1, weightedDistance);
expectedWeightedDistancesMapFP2.put(facet3, weightedDistance);
expectedWeightedDistancesMapFP3.put(facet1, weightedDistance);
@@ -391,7 +414,11 @@ public class HausdorffDistancePrioritizedTest {
expectedMergedPrioritiesMap.put(facet3, mergedPriorities);
expectedMergedPrioritiesMap.put(facet4, mergedPriorities);
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, true, false);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ true,
+ false);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}
@@ -428,14 +455,14 @@ public class HausdorffDistancePrioritizedTest {
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP3 = new HashMap<>();
final Map<MeshFacet, Double> expectedWeightedDistancesMapFP4 = new HashMap<>();
for (final MeshFacet facet: facets) {
- expectedWeightedDistancesMapFP2.put(facet, 0d);
- expectedWeightedDistancesMapFP3.put(facet, 0d);
- expectedWeightedDistancesMapFP4.put(facet, 0d);
+ expectedWeightedDistancesMapFP2.put(facet, Double.NaN);
+ expectedWeightedDistancesMapFP3.put(facet, Double.NaN);
+ expectedWeightedDistancesMapFP4.put(facet, Double.NaN);
}
- final double weightedDistance = 0 + 0.09 + 0.16 + 0.21 + 0.24 + 0.25 + 0.24 + 0.21 + 0.16 + 0.09 + 0 + 0.09;
+ final double weightedDistance = (0 + 0.01 + 0.04 + 0.09 + 0.16 + 0.25 + 0.36 + 0.49 + 0.64 + 0.81 + 1 + 0.99) / 11;
expectedWeightedDistancesMapFP2.put(facet1, weightedDistance);
expectedWeightedDistancesMapFP3.put(facet3, weightedDistance);
- expectedWeightedDistancesMapFP4.put(facet5, weightedDistance);
+ expectedWeightedDistancesMapFP4.put(facet5, -weightedDistance);
final Map<FeaturePointType, Map<MeshFacet, Double>> expectedFeaturePointsWeights = Map.of(fpType1, expectedWeightedDistancesMapFP1,
fpType2, expectedWeightedDistancesMapFP2,
fpType3, expectedWeightedDistancesMapFP3,
@@ -450,7 +477,11 @@ public class HausdorffDistancePrioritizedTest {
expectedMergedPrioritiesMap.put(facet3, mergedPriorities);
expectedMergedPrioritiesMap.put(facet5, mergedPriorities);
- final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(face, new HashSet<>(featurePointTypes), POINT_TO_POINT, false, true);
+ final HausdorffDistancePrioritized visitor = new HausdorffDistancePrioritized(getHumanFace(facets2, List.of(), List.of()),
+ new HashSet<>(featurePointTypes),
+ POINT_TO_POINT,
+ true,
+ true);
performTest(face, expectedPriorities, expectedFeaturePointsWeights, expectedMergedPrioritiesMap, visitor);
}