1 // Ceres Solver - A fast non-linear least squares minimizer 2 // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. 3 // http://code.google.com/p/ceres-solver/ 4 // 5 // Redistribution and use in source and binary forms, with or without 6 // modification, are permitted provided that the following conditions are met: 7 // 8 // * Redistributions of source code must retain the above copyright notice, 9 // this list of conditions and the following disclaimer. 10 // * Redistributions in binary form must reproduce the above copyright notice, 11 // this list of conditions and the following disclaimer in the documentation 12 // and/or other materials provided with the distribution. 13 // * Neither the name of Google Inc. nor the names of its contributors may be 14 // used to endorse or promote products derived from this software without 15 // specific prior written permission. 16 // 17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 27 // POSSIBILITY OF SUCH DAMAGE. 28 // 29 // Author: Sameer Agarwal (sameeragarwal (at) google.com) 30 // David Gallup (dgallup (at) google.com) 31 32 // This include must come before any #ifndef check on Ceres compile options. 33 #include "ceres/internal/port.h" 34 35 #ifndef CERES_NO_SUITESPARSE 36 37 #include "ceres/canonical_views_clustering.h" 38 39 #include "ceres/collections_port.h" 40 #include "ceres/graph.h" 41 #include "gtest/gtest.h" 42 43 namespace ceres { 44 namespace internal { 45 46 const int kVertexIds[] = {0, 1, 2, 3}; 47 class CanonicalViewsTest : public ::testing::Test { 48 protected: 49 virtual void SetUp() { 50 // The graph structure is as follows. 51 // 52 // Vertex weights: 0 2 2 0 53 // V0-----V1-----V2-----V3 54 // Edge weights: 0.8 0.9 0.3 55 const double kVertexWeights[] = {0.0, 2.0, 2.0, -1.0}; 56 for (int i = 0; i < 4; ++i) { 57 graph_.AddVertex(i, kVertexWeights[i]); 58 } 59 // Create self edges. 60 // CanonicalViews requires that every view "sees" itself. 61 for (int i = 0; i < 4; ++i) { 62 graph_.AddEdge(i, i, 1.0); 63 } 64 65 // Create three edges. 66 const double kEdgeWeights[] = {0.8, 0.9, 0.3}; 67 for (int i = 0; i < 3; ++i) { 68 // The graph interface is directed, so remember to create both 69 // edges. 70 graph_.AddEdge(kVertexIds[i], kVertexIds[i + 1], kEdgeWeights[i]); 71 } 72 } 73 74 void ComputeClustering() { 75 ComputeCanonicalViewsClustering(options_, graph_, ¢ers_, &membership_); 76 } 77 78 Graph<int> graph_; 79 80 CanonicalViewsClusteringOptions options_; 81 vector<int> centers_; 82 HashMap<int, int> membership_; 83 }; 84 85 TEST_F(CanonicalViewsTest, ComputeCanonicalViewsTest) { 86 options_.min_views = 0; 87 options_.size_penalty_weight = 0.5; 88 options_.similarity_penalty_weight = 0.0; 89 options_.view_score_weight = 0.0; 90 ComputeClustering(); 91 92 // 2 canonical views. 93 EXPECT_EQ(centers_.size(), 2); 94 EXPECT_EQ(centers_[0], kVertexIds[1]); 95 EXPECT_EQ(centers_[1], kVertexIds[3]); 96 97 // Check cluster membership. 98 EXPECT_EQ(FindOrDie(membership_, kVertexIds[0]), 0); 99 EXPECT_EQ(FindOrDie(membership_, kVertexIds[1]), 0); 100 EXPECT_EQ(FindOrDie(membership_, kVertexIds[2]), 0); 101 EXPECT_EQ(FindOrDie(membership_, kVertexIds[3]), 1); 102 } 103 104 // Increases size penalty so the second canonical view won't be 105 // chosen. 106 TEST_F(CanonicalViewsTest, SizePenaltyTest) { 107 options_.min_views = 0; 108 options_.size_penalty_weight = 2.0; 109 options_.similarity_penalty_weight = 0.0; 110 options_.view_score_weight = 0.0; 111 ComputeClustering(); 112 113 // 1 canonical view. 114 EXPECT_EQ(centers_.size(), 1); 115 EXPECT_EQ(centers_[0], kVertexIds[1]); 116 } 117 118 119 // Increases view score weight so vertex 2 will be chosen. 120 TEST_F(CanonicalViewsTest, ViewScoreTest) { 121 options_.min_views = 0; 122 options_.size_penalty_weight = 0.5; 123 options_.similarity_penalty_weight = 0.0; 124 options_.view_score_weight = 1.0; 125 ComputeClustering(); 126 127 // 2 canonical views. 128 EXPECT_EQ(centers_.size(), 2); 129 EXPECT_EQ(centers_[0], kVertexIds[1]); 130 EXPECT_EQ(centers_[1], kVertexIds[2]); 131 } 132 133 // Increases similarity penalty so vertex 2 won't be chosen despite 134 // it's view score. 135 TEST_F(CanonicalViewsTest, SimilarityPenaltyTest) { 136 options_.min_views = 0; 137 options_.size_penalty_weight = 0.5; 138 options_.similarity_penalty_weight = 3.0; 139 options_.view_score_weight = 1.0; 140 ComputeClustering(); 141 142 // 2 canonical views. 143 EXPECT_EQ(centers_.size(), 1); 144 EXPECT_EQ(centers_[0], kVertexIds[1]); 145 } 146 147 } // namespace internal 148 } // namespace ceres 149 150 #endif // CERES_NO_SUITESPARSE 151
