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.CoordinatesType;
19 import com.irurueta.geometry.PinholeCamera;
20 import com.irurueta.geometry.Point2D;
21 import com.irurueta.geometry.Point3D;
22 import com.irurueta.numerical.robust.LMedSRobustEstimator;
23 import com.irurueta.numerical.robust.LMedSRobustEstimatorListener;
24 import com.irurueta.numerical.robust.RobustEstimator;
25 import com.irurueta.numerical.robust.RobustEstimatorException;
26 import com.irurueta.numerical.robust.RobustEstimatorMethod;
27
28 import java.util.ArrayList;
29 import java.util.List;
30
31 /**
32 * Finds the best pinhole camera for provided collections of matched 2D/3D
33 * points using LMedS + DLT algorithms.
34 */
35 @SuppressWarnings("DuplicatedCode")
36 public class LMedSDLTPointCorrespondencePinholeCameraRobustEstimator extends
37 DLTPointCorrespondencePinholeCameraRobustEstimator {
38
39 /**
40 * Default value to be used for stop threshold. Stop threshold can be used
41 * to keep the algorithm iterating in case that best estimated threshold
42 * using median of residuals is not small enough. Once a solution is found
43 * that generates a threshold below this value, the algorithm will stop.
44 * The stop threshold can be used to prevent the LMedS algorithm iterating
45 * too many times in cases where samples have a very similar accuracy.
46 * For instance, in cases where proportion of outliers is very small (close
47 * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
48 * iterate for a long time trying to find the best solution when indeed
49 * there is no need to do that if a reasonable threshold has already been
50 * reached.
51 * Because of this behaviour the stop threshold can be set to a value much
52 * lower than the one typically used in RANSAC, and yet the algorithm could
53 * still produce even smaller thresholds in estimated results.
54 */
55 public static final double DEFAULT_STOP_THRESHOLD = 1.0;
56
57 /**
58 * Minimum allowed stop threshold value.
59 */
60 public static final double MIN_STOP_THRESHOLD = 0.0;
61
62 /**
63 * Threshold to be used to keep the algorithm iterating in case that best
64 * estimated threshold using median of residuals is not small enough. Once
65 * a solution is found that generates a threshold below this value, the
66 * algorithm will stop.
67 * The stop threshold can be used to prevent the LMedS algorithm iterating
68 * too many times in cases where samples have a very similar accuracy.
69 * For instance, in cases where proportion of outliers is very small (close
70 * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
71 * iterate for a long time trying to find the best solution when indeed
72 * there is no need to do that if a reasonable threshold has already been
73 * reached.
74 * Because of this behaviour the stop threshold can be set to a value much
75 * lower than the one typically used in RANSAC, and yet the algorithm could
76 * still produce even smaller thresholds in estimated results.
77 */
78 private double stopThreshold;
79
80 /**
81 * Constructor.
82 */
83 public LMedSDLTPointCorrespondencePinholeCameraRobustEstimator() {
84 super();
85 stopThreshold = DEFAULT_STOP_THRESHOLD;
86 }
87
88 /**
89 * Constructor with lists of points to be used to estimate a pinhole camera.
90 * Points in the list located at the same position are considered to be
91 * matched. Hence, both lists must have the same size, and their size must
92 * be greater or equal than MIN_NUMBER_OF_POINT_CORRESPONDENCES.
93 *
94 * @param points3D list of 3D points used to estimate a pinhole camera.
95 * @param points2D list of corresponding projected 2D points used to
96 * estimate a pinhole camera.
97 * @throws IllegalArgumentException if provided lists of points don't have
98 * the same size or their size is smaller than required minimum size
99 * (6 correspondences).
100 */
101 public LMedSDLTPointCorrespondencePinholeCameraRobustEstimator(
102 final List<Point3D> points3D, final List<Point2D> points2D) {
103 super(points3D, points2D);
104 stopThreshold = DEFAULT_STOP_THRESHOLD;
105 }
106
107 /**
108 * Constructor.
109 *
110 * @param listener listener to be notified of events such as when estimation
111 * starts, ends or its progress significantly changes.
112 */
113 public LMedSDLTPointCorrespondencePinholeCameraRobustEstimator(
114 final PinholeCameraRobustEstimatorListener listener) {
115 super(listener);
116 stopThreshold = DEFAULT_STOP_THRESHOLD;
117 }
118
119 /**
120 * Constructor with listener and lists of points to be used ot estimate a
121 * pinhole camera.
122 * Points in the list located at the same position are considered to be
123 * matched. Hence, both lists must have the same size, and their size must
124 * be greater or equal than MIN_NUMBER_OF_POINT_CORRESPONDENCES.
125 *
126 * @param listener listener to be notified of events such as when estimation
127 * starts, ends or its progress significantly changes.
128 * @param points3D list of 3D points used to estimate a pinhole camera.
129 * @param points2D list of corresponding projected 2D points used to
130 * estimate a pinhole camera.
131 * @throws IllegalArgumentException if provided lists of points don't have
132 * the same size or their size is smaller than required minimum size
133 * (6 correspondences).
134 */
135 public LMedSDLTPointCorrespondencePinholeCameraRobustEstimator(
136 final PinholeCameraRobustEstimatorListener listener,
137 final List<Point3D> points3D, final List<Point2D> points2D) {
138 super(listener, points3D, points2D);
139 stopThreshold = DEFAULT_STOP_THRESHOLD;
140 }
141
142 /**
143 * Returns threshold to be used to keep the algorithm iterating in case that
144 * best estimated threshold using median of residuals is not small enough.
145 * Once a solution is found that generates a threshold below this value, the
146 * algorithm will stop.
147 * The stop threshold can be used to prevent the LMedS algorithm iterating
148 * too many times in cases where samples have a very similar accuracy.
149 * For instance, in cases where proportion of outliers is very small (close
150 * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
151 * iterate for a long time trying to find the best solution when indeed
152 * there is no need to do that if a reasonable threshold has already been
153 * reached.
154 * Because of this behaviour the stop threshold can be set to a value much
155 * lower than the one typically used in RANSAC, and yet the algorithm could
156 * still produce even smaller thresholds in estimated results.
157 *
158 * @return stop threshold to stop the algorithm prematurely when a certain
159 * accuracy has been reached.
160 */
161 public double getStopThreshold() {
162 return stopThreshold;
163 }
164
165 /**
166 * Sets threshold to be used to keep the algorithm iterating in case that
167 * best estimated threshold using median of residuals is not small enough.
168 * Once a solution is found that generates a threshold below this value, the
169 * algorithm will stop.
170 * The stop threshold can be used to prevent the LMedS algorithm iterating
171 * too many times in cases where samples have a very similar accuracy.
172 * For instance, in cases where proportion of outliers is very small (close
173 * to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would
174 * iterate for a long time trying to find the best solution when indeed
175 * there is no need to do that if a reasonable threshold has already been
176 * reached.
177 * Because of this behaviour the stop threshold can be set to a value much
178 * lower than the one typically used in RANSAC, and yet the algorithm could
179 * still produce even smaller thresholds in estimated results.
180 *
181 * @param stopThreshold stop threshold to stop the algorithm prematurely
182 * when a certain accuracy has been reached.
183 * @throws IllegalArgumentException if provided value is zero or negative.
184 * @throws LockedException if robust estimator is locked because an
185 * estimation is already in progress.
186 */
187 public void setStopThreshold(final double stopThreshold) throws LockedException {
188 if (isLocked()) {
189 throw new LockedException();
190 }
191 if (stopThreshold <= MIN_STOP_THRESHOLD) {
192 throw new IllegalArgumentException();
193 }
194
195 this.stopThreshold = stopThreshold;
196 }
197
198 /**
199 * Estimates a pinhole camera using a robust estimator and
200 * the best set of matched 2D/3D point correspondences or 2D line/3D plane
201 * correspondences found using the robust estimator.
202 *
203 * @return a pinhole camera.
204 * @throws LockedException if robust estimator is locked because an
205 * estimation is already in progress.
206 * @throws NotReadyException if provided input data is not enough to start
207 * the estimation.
208 * @throws RobustEstimatorException if estimation fails for any reason
209 * (i.e. numerical instability, no solution available, etc).
210 */
211 @Override
212 public PinholeCamera estimate() throws LockedException, NotReadyException, RobustEstimatorException {
213 if (isLocked()) {
214 throw new LockedException();
215 }
216 if (!isReady()) {
217 throw new NotReadyException();
218 }
219
220 // pinhole camera estimator using DLT (Direct Linear Transform) algorithm
221 final var nonRobustEstimator = new DLTPointCorrespondencePinholeCameraEstimator();
222
223 nonRobustEstimator.setLMSESolutionAllowed(false);
224 nonRobustEstimator.setPointCorrespondencesNormalized(normalizeSubsetPointCorrespondences);
225
226 // suggestions
227 nonRobustEstimator.setSuggestSkewnessValueEnabled(isSuggestSkewnessValueEnabled());
228 nonRobustEstimator.setSuggestedSkewnessValue(getSuggestedSkewnessValue());
229 nonRobustEstimator.setSuggestHorizontalFocalLengthEnabled(isSuggestHorizontalFocalLengthEnabled());
230 nonRobustEstimator.setSuggestedHorizontalFocalLengthValue(getSuggestedHorizontalFocalLengthValue());
231 nonRobustEstimator.setSuggestVerticalFocalLengthEnabled(isSuggestVerticalFocalLengthEnabled());
232 nonRobustEstimator.setSuggestedVerticalFocalLengthValue(getSuggestedVerticalFocalLengthValue());
233 nonRobustEstimator.setSuggestAspectRatioEnabled(isSuggestAspectRatioEnabled());
234 nonRobustEstimator.setSuggestedAspectRatioValue(getSuggestedAspectRatioValue());
235 nonRobustEstimator.setSuggestPrincipalPointEnabled(isSuggestPrincipalPointEnabled());
236 nonRobustEstimator.setSuggestedPrincipalPointValue(getSuggestedPrincipalPointValue());
237 nonRobustEstimator.setSuggestRotationEnabled(isSuggestRotationEnabled());
238 nonRobustEstimator.setSuggestedRotationValue(getSuggestedRotationValue());
239 nonRobustEstimator.setSuggestCenterEnabled(isSuggestCenterEnabled());
240 nonRobustEstimator.setSuggestedCenterValue(getSuggestedCenterValue());
241
242 final var innerEstimator = new LMedSRobustEstimator<>(new LMedSRobustEstimatorListener<PinholeCamera>() {
243
244 // point to be reused when computing residuals
245 private final Point2D testPoint = Point2D.create(CoordinatesType.HOMOGENEOUS_COORDINATES);
246
247 // 3D points for a subset of samples
248 private final List<Point3D> subset3D = new ArrayList<>();
249
250 // 2D points for a subset of samples
251 private final List<Point2D> subset2D = new ArrayList<>();
252
253 @Override
254 public int getTotalSamples() {
255 return points3D.size();
256 }
257
258 @Override
259 public int getSubsetSize() {
260 return PointCorrespondencePinholeCameraRobustEstimator.MIN_NUMBER_OF_POINT_CORRESPONDENCES;
261 }
262
263 @Override
264 public void estimatePreliminarSolutions(final int[] samplesIndices, final List<PinholeCamera> solutions) {
265 subset3D.clear();
266 subset3D.add(points3D.get(samplesIndices[0]));
267 subset3D.add(points3D.get(samplesIndices[1]));
268 subset3D.add(points3D.get(samplesIndices[2]));
269 subset3D.add(points3D.get(samplesIndices[3]));
270 subset3D.add(points3D.get(samplesIndices[4]));
271 subset3D.add(points3D.get(samplesIndices[5]));
272
273 subset2D.clear();
274 subset2D.add(points2D.get(samplesIndices[0]));
275 subset2D.add(points2D.get(samplesIndices[1]));
276 subset2D.add(points2D.get(samplesIndices[2]));
277 subset2D.add(points2D.get(samplesIndices[3]));
278 subset2D.add(points2D.get(samplesIndices[4]));
279 subset2D.add(points2D.get(samplesIndices[5]));
280
281 try {
282 nonRobustEstimator.setLists(subset3D, subset2D);
283
284 final var cam = nonRobustEstimator.estimate();
285 solutions.add(cam);
286 } catch (final Exception e) {
287 // if points configuration is degenerate, no solution is added
288 }
289 }
290
291 @Override
292 public double computeResidual(final PinholeCamera currentEstimation, final int i) {
293 // pick i-th points
294 final var point3D = points3D.get(i);
295 final var point2D = points2D.get(i);
296
297 // project point3D into test point
298 currentEstimation.project(point3D, testPoint);
299
300 // compare test point and 2D point
301 return testPoint.distanceTo(point2D);
302 }
303
304 @Override
305 public boolean isReady() {
306 return LMedSDLTPointCorrespondencePinholeCameraRobustEstimator.this.isReady();
307 }
308
309 @Override
310 public void onEstimateStart(final RobustEstimator<PinholeCamera> estimator) {
311 if (listener != null) {
312 listener.onEstimateStart(LMedSDLTPointCorrespondencePinholeCameraRobustEstimator.this);
313 }
314 }
315
316 @Override
317 public void onEstimateEnd(final RobustEstimator<PinholeCamera> estimator) {
318 if (listener != null) {
319 listener.onEstimateEnd(LMedSDLTPointCorrespondencePinholeCameraRobustEstimator.this);
320 }
321 }
322
323 @Override
324 public void onEstimateNextIteration(final RobustEstimator<PinholeCamera> estimator, final int iteration) {
325 if (listener != null) {
326 listener.onEstimateNextIteration(
327 LMedSDLTPointCorrespondencePinholeCameraRobustEstimator.this, iteration);
328 }
329 }
330
331 @Override
332 public void onEstimateProgressChange(final RobustEstimator<PinholeCamera> estimator, final float progress) {
333 if (listener != null) {
334 listener.onEstimateProgressChange(
335 LMedSDLTPointCorrespondencePinholeCameraRobustEstimator.this, progress);
336 }
337 }
338 });
339
340 try {
341 locked = true;
342 inliersData = null;
343 innerEstimator.setConfidence(confidence);
344 innerEstimator.setMaxIterations(maxIterations);
345 innerEstimator.setProgressDelta(progressDelta);
346 innerEstimator.setStopThreshold(stopThreshold);
347 final var result = innerEstimator.estimate();
348 inliersData = innerEstimator.getInliersData();
349 return attemptRefine(result, nonRobustEstimator.getMaxSuggestionWeight());
350 } catch (final com.irurueta.numerical.LockedException e) {
351 throw new LockedException(e);
352 } catch (final com.irurueta.numerical.NotReadyException e) {
353 throw new NotReadyException(e);
354 } finally {
355 locked = false;
356 }
357 }
358
359 /**
360 * Returns method being used for robust estimation.
361 *
362 * @return method being used for robust estimation.
363 */
364 @Override
365 public RobustEstimatorMethod getMethod() {
366 return RobustEstimatorMethod.LMEDS;
367 }
368
369 /**
370 * Gets standard deviation used for Levenberg-Marquardt fitting during
371 * refinement.
372 * Returned value gives an indication of how much variance each residual
373 * has.
374 * Typically, this value is related to the threshold used on each robust
375 * estimation, since residuals of found inliers are within the range of
376 * such threshold.
377 *
378 * @return standard deviation used for refinement.
379 */
380 @Override
381 protected double getRefinementStandardDeviation() {
382 final var inliersData = (LMedSRobustEstimator.LMedSInliersData) getInliersData();
383
384 // avoid setting a threshold too strict
385 final var threshold = inliersData.getEstimatedThreshold();
386 return Math.max(threshold, stopThreshold);
387 }
388 }