1 /*
2 * Copyright (C) 2015 Alberto Irurueta Carro (alberto@irurueta.com)
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16 package com.irurueta.geometry.estimators;
17
18 import com.irurueta.geometry.CoplanarPointsException;
19 import com.irurueta.geometry.Point3D;
20 import com.irurueta.geometry.Sphere;
21 import com.irurueta.numerical.robust.MSACRobustEstimator;
22 import com.irurueta.numerical.robust.MSACRobustEstimatorListener;
23 import com.irurueta.numerical.robust.RobustEstimator;
24 import com.irurueta.numerical.robust.RobustEstimatorException;
25 import com.irurueta.numerical.robust.RobustEstimatorMethod;
26
27 import java.util.List;
28
29 /**
30 * Finds the best sphere for provided collection of 3D points using MSAC
31 * algorithm.
32 */
33 @SuppressWarnings("DuplicatedCode")
34 public class MSACSphereRobustEstimator extends SphereRobustEstimator {
35 /**
36 * Constant defining default threshold to determine whether points are
37 * inliers or not.
38 * Because typical resolution for points is 1 voxel, then default threshold
39 * is defined as 1.
40 */
41 public static final double DEFAULT_THRESHOLD = 1.0;
42
43 /**
44 * Minimum value that can be set as threshold.
45 * Threshold must be strictly greater than 0.0.
46 */
47 public static final double MIN_THRESHOLD = 0.0;
48
49 /**
50 * Threshold to determine whether points are inliers or not when testing
51 * possible estimation solutions.
52 * The threshold refers to the amount of error (i.e. distance) a possible
53 * solution has on a matched pair of points.
54 */
55 private double threshold;
56
57 /**
58 * Constructor.
59 */
60 public MSACSphereRobustEstimator() {
61 super();
62 threshold = DEFAULT_THRESHOLD;
63 }
64
65 /**
66 * Constructor with points.
67 *
68 * @param points 3D points to estimate a sphere.
69 * @throws IllegalArgumentException if provided list of points don't have
70 * a size greater or equal than MINIMUM_SIZE.
71 */
72 public MSACSphereRobustEstimator(final List<Point3D> points) {
73 super(points);
74 threshold = DEFAULT_THRESHOLD;
75 }
76
77 /**
78 * Constructor.
79 *
80 * @param listener listener to be notified of events such as when estimation
81 * starts, ends or its progress significantly changes.
82 */
83 public MSACSphereRobustEstimator(final SphereRobustEstimatorListener listener) {
84 super(listener);
85 threshold = DEFAULT_THRESHOLD;
86 }
87
88
89 /**
90 * Constructor
91 *
92 * @param listener listener to be notified of events such as when estimation
93 * starts, ends or its progress significantly changes.
94 * @param points 3D points to estimate a sphere.
95 * @throws IllegalArgumentException if provided list of points don't have
96 * a size greater or equal than MINIMUM_SIZE.
97 */
98 public MSACSphereRobustEstimator(final SphereRobustEstimatorListener listener, final List<Point3D> points) {
99 super(listener, points);
100 threshold = DEFAULT_THRESHOLD;
101 }
102
103 /**
104 * Returns threshold to determine whether points are inliers or not when
105 * testing possible estimation solutions.
106 * The threshold refers to the amount of error a possible solution has on a
107 * given point.
108 *
109 * @return threshold to determine whether points are inliers or not when
110 * testing possible estimation solutions.
111 */
112 public double getThreshold() {
113 return threshold;
114 }
115
116 /**
117 * Sets threshold to determine whether points are inliers or not when
118 * testing possible estimation solutions.
119 * The threshold refers to the amount of error a possible solution has on
120 * a given point.
121 *
122 * @param threshold threshold to be set.
123 * @throws IllegalArgumentException if provided value is equal or less than
124 * zero.
125 * @throws LockedException if robust estimator is locked because an
126 * estimation is already in progress.
127 */
128 public void setThreshold(final double threshold) throws LockedException {
129 if (isLocked()) {
130 throw new LockedException();
131 }
132 if (threshold <= MIN_THRESHOLD) {
133 throw new IllegalArgumentException();
134 }
135 this.threshold = threshold;
136 }
137
138
139 /**
140 * Estimates a sphere using a robust estimator and the best set of 3D points
141 * that fit into the locus of the estimated sphere found using the robust
142 * estimator.
143 *
144 * @return a sphere.
145 * @throws LockedException if robust estimator is locked because an
146 * estimation is already in progress.
147 * @throws NotReadyException if provided input data is not enough to start
148 * the estimation.
149 * @throws RobustEstimatorException if estimation fails for any reason
150 * (i.e. numerical instability, no solution available, etc).
151 */
152 @Override
153 public Sphere estimate() throws LockedException, NotReadyException, RobustEstimatorException {
154 if (isLocked()) {
155 throw new LockedException();
156 }
157 if (!isReady()) {
158 throw new NotReadyException();
159 }
160
161 final var innerEstimator = new MSACRobustEstimator<>(new MSACRobustEstimatorListener<Sphere>() {
162
163 @Override
164 public double getThreshold() {
165 return threshold;
166 }
167
168 @Override
169 public int getTotalSamples() {
170 return points.size();
171 }
172
173 @Override
174 public int getSubsetSize() {
175 return SphereRobustEstimator.MINIMUM_SIZE;
176 }
177
178 @Override
179 public void estimatePreliminarSolutions(final int[] samplesIndices, final List<Sphere> solutions) {
180 final var point1 = points.get(samplesIndices[0]);
181 final var point2 = points.get(samplesIndices[1]);
182 final var point3 = points.get(samplesIndices[2]);
183 final var point4 = points.get(samplesIndices[3]);
184
185 try {
186 final var sphere = new Sphere(point1, point2, point3, point4);
187 solutions.add(sphere);
188 } catch (final CoplanarPointsException e) {
189 // if points are coincident, no solution is added
190 }
191 }
192
193 @Override
194 public double computeResidual(final Sphere currentEstimation, final int i) {
195 return residual(currentEstimation, points.get(i));
196 }
197
198 @Override
199 public boolean isReady() {
200 return MSACSphereRobustEstimator.this.isReady();
201 }
202
203 @Override
204 public void onEstimateStart(final RobustEstimator<Sphere> estimator) {
205 if (listener != null) {
206 listener.onEstimateStart(MSACSphereRobustEstimator.this);
207 }
208 }
209
210 @Override
211 public void onEstimateEnd(final RobustEstimator<Sphere> estimator) {
212 if (listener != null) {
213 listener.onEstimateEnd(MSACSphereRobustEstimator.this);
214 }
215 }
216
217 @Override
218 public void onEstimateNextIteration(final RobustEstimator<Sphere> estimator, final int iteration) {
219 if (listener != null) {
220 listener.onEstimateNextIteration(MSACSphereRobustEstimator.this, iteration);
221 }
222 }
223
224 @Override
225 public void onEstimateProgressChange(final RobustEstimator<Sphere> estimator, final float progress) {
226 if (listener != null) {
227 listener.onEstimateProgressChange(MSACSphereRobustEstimator.this, progress);
228 }
229 }
230 });
231
232 try {
233 locked = true;
234 innerEstimator.setConfidence(confidence);
235 innerEstimator.setMaxIterations(maxIterations);
236 innerEstimator.setProgressDelta(progressDelta);
237 return innerEstimator.estimate();
238 } catch (final com.irurueta.numerical.LockedException e) {
239 throw new LockedException(e);
240 } catch (final com.irurueta.numerical.NotReadyException e) {
241 throw new NotReadyException(e);
242 } finally {
243 locked = false;
244 }
245 }
246
247 /**
248 * Returns method being used for robust estimation.
249 *
250 * @return method being used for robust estimation.
251 */
252 @Override
253 public RobustEstimatorMethod getMethod() {
254 return RobustEstimatorMethod.MSAC;
255 }
256 }