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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.CoincidentPlanesException;
19  import com.irurueta.geometry.DualQuadric;
20  import com.irurueta.geometry.Plane;
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 dual quadric for provided collection of 3D planes using MSAC
31   * algorithm.
32   */
33  @SuppressWarnings("DuplicatedCode")
34  public class MSACDualQuadricRobustEstimator extends DualQuadricRobustEstimator {
35      /**
36       * Constant defining default threshold to determine whether planes are
37       * inliers or not.
38       * Threshold is defined by the equation abs(trans(P) * dQ * P) < t, where
39       * trans is the transposition, P is a plane, dQ is a dual quadric and t is a
40       * threshold.
41       * This equation determines the planes P belonging to the locus of a dual
42       * quadric dQ up to a certain threshold.
43       */
44      public static final double DEFAULT_THRESHOLD = 1e-7;
45  
46      /**
47       * Minimum value that can be set as threshold.
48       * Threshold must be strictly greater than 0.0.
49       */
50      public static final double MIN_THRESHOLD = 0.0;
51  
52      /**
53       * Threshold to determine whether planes are inliers or not when testing
54       * possible estimation solutions.
55       * The threshold refers to the amount of algebraic error a possible
56       * solution has on a given line.
57       */
58      private double threshold;
59  
60      /**
61       * Constructor.
62       */
63      public MSACDualQuadricRobustEstimator() {
64          super();
65          threshold = DEFAULT_THRESHOLD;
66      }
67  
68      /**
69       * Constructor with points.
70       *
71       * @param planes 3D planes to estimate a dual quadric.
72       * @throws IllegalArgumentException if provided list of planes don't have
73       *                                  a size greater or equal than MINIMUM_SIZE.
74       */
75      public MSACDualQuadricRobustEstimator(final List<Plane> planes) {
76          super(planes);
77          threshold = DEFAULT_THRESHOLD;
78      }
79  
80      /**
81       * Constructor.
82       *
83       * @param listener listener to be notified of events such as when estimation
84       *                 starts, ends or its progress significantly changes.
85       */
86      public MSACDualQuadricRobustEstimator(final DualQuadricRobustEstimatorListener listener) {
87          super(listener);
88          threshold = DEFAULT_THRESHOLD;
89      }
90  
91  
92      /**
93       * Constructor.
94       *
95       * @param listener listener to be notified of events such as when estimation
96       *                 starts, ends or its progress significantly changes.
97       * @param planes   3D planes to estimate a dual quadric.
98       * @throws IllegalArgumentException if provided list of planes don't have
99       *                                  a size greater or equal than MINIMUM_SIZE.
100      */
101     public MSACDualQuadricRobustEstimator(
102             final DualQuadricRobustEstimatorListener listener, final List<Plane> planes) {
103         super(listener, planes);
104         threshold = DEFAULT_THRESHOLD;
105     }
106 
107     /**
108      * Returns threshold to determine whether planes are inliers or not when
109      * testing possible estimation solutions.
110      * The threshold refers to the amount of error a possible solution has on a
111      * given plane.
112      *
113      * @return threshold to determine whether planes are inliers or not when
114      * testing possible estimation solutions.
115      */
116     public double getThreshold() {
117         return threshold;
118     }
119 
120     /**
121      * Sets threshold to determine whether planes are inliers or not when
122      * testing possible estimation solutions.
123      * The threshold refers to the amount of algebraic error a possible
124      * solution has on a given plane.
125      *
126      * @param threshold threshold to be set.
127      * @throws IllegalArgumentException if provided value is equal or less than
128      *                                  zero.
129      * @throws LockedException          if robust estimator is locked because an
130      *                                  estimation is already in progress.
131      */
132     public void setThreshold(final double threshold) throws LockedException {
133         if (isLocked()) {
134             throw new LockedException();
135         }
136         if (threshold <= MIN_THRESHOLD) {
137             throw new IllegalArgumentException();
138         }
139         this.threshold = threshold;
140     }
141 
142 
143     /**
144      * Estimates a dual quadric using a robust estimator and the best set of 3D
145      * planes that fit into the locus of the estimated dual quadric found using
146      * the robust estimator.
147      *
148      * @return a dual quadric.
149      * @throws LockedException          if robust estimator is locked because an
150      *                                  estimation is already in progress.
151      * @throws NotReadyException        if provided input data is not enough to start
152      *                                  the estimation.
153      * @throws RobustEstimatorException if estimation fails for any reason
154      *                                  (i.e. numerical instability, no solution available, etc).
155      */
156     @Override
157     public DualQuadric estimate() throws LockedException, NotReadyException, RobustEstimatorException {
158         if (isLocked()) {
159             throw new LockedException();
160         }
161         if (!isReady()) {
162             throw new NotReadyException();
163         }
164 
165         final var innerEstimator = new MSACRobustEstimator<>(new MSACRobustEstimatorListener<DualQuadric>() {
166 
167             @Override
168             public double getThreshold() {
169                 return threshold;
170             }
171 
172             @Override
173             public int getTotalSamples() {
174                 return planes.size();
175             }
176 
177             @Override
178             public int getSubsetSize() {
179                 return DualQuadricRobustEstimator.MINIMUM_SIZE;
180             }
181 
182             @Override
183             public void estimatePreliminarSolutions(final int[] samplesIndices, final List<DualQuadric> solutions) {
184                 final var plane1 = planes.get(samplesIndices[0]);
185                 final var plane2 = planes.get(samplesIndices[1]);
186                 final var plane3 = planes.get(samplesIndices[2]);
187                 final var plane4 = planes.get(samplesIndices[3]);
188                 final var plane5 = planes.get(samplesIndices[4]);
189                 final var plane6 = planes.get(samplesIndices[5]);
190                 final var plane7 = planes.get(samplesIndices[6]);
191                 final var plane8 = planes.get(samplesIndices[7]);
192                 final var plane9 = planes.get(samplesIndices[8]);
193 
194                 try {
195                     final var dualQuadric = new DualQuadric(plane1, plane2, plane3, plane4, plane5, plane6, plane7,
196                             plane8, plane9);
197                     solutions.add(dualQuadric);
198                 } catch (final CoincidentPlanesException e) {
199                     // if points are coincident, no solution is added
200                 }
201             }
202 
203             @Override
204             public double computeResidual(final DualQuadric currentEstimation, final int i) {
205                 return residual(currentEstimation, planes.get(i));
206             }
207 
208             @Override
209             public boolean isReady() {
210                 return MSACDualQuadricRobustEstimator.this.isReady();
211             }
212 
213             @Override
214             public void onEstimateStart(final RobustEstimator<DualQuadric> estimator) {
215                 if (listener != null) {
216                     listener.onEstimateStart(MSACDualQuadricRobustEstimator.this);
217                 }
218             }
219 
220             @Override
221             public void onEstimateEnd(final RobustEstimator<DualQuadric> estimator) {
222                 if (listener != null) {
223                     listener.onEstimateEnd(MSACDualQuadricRobustEstimator.this);
224                 }
225             }
226 
227             @Override
228             public void onEstimateNextIteration(final RobustEstimator<DualQuadric> estimator, final int iteration) {
229                 if (listener != null) {
230                     listener.onEstimateNextIteration(MSACDualQuadricRobustEstimator.this, iteration);
231                 }
232             }
233 
234             @Override
235             public void onEstimateProgressChange(final RobustEstimator<DualQuadric> estimator, final float progress) {
236                 if (listener != null) {
237                     listener.onEstimateProgressChange(MSACDualQuadricRobustEstimator.this, progress);
238                 }
239             }
240         });
241 
242         try {
243             locked = true;
244             innerEstimator.setConfidence(confidence);
245             innerEstimator.setMaxIterations(maxIterations);
246             innerEstimator.setProgressDelta(progressDelta);
247             return innerEstimator.estimate();
248         } catch (final com.irurueta.numerical.LockedException e) {
249             throw new LockedException(e);
250         } catch (final com.irurueta.numerical.NotReadyException e) {
251             throw new NotReadyException(e);
252         } finally {
253             locked = false;
254         }
255     }
256 
257     /**
258      * Returns method being used for robust estimation.
259      *
260      * @return method being used for robust estimation.
261      */
262     @Override
263     public RobustEstimatorMethod getMethod() {
264         return RobustEstimatorMethod.MSAC;
265     }
266 }