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annotate trajectorymanagement/src/LCSMetric.h @ 1211:a095d4fbb2ea

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author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Tue, 02 May 2023 07:12:26 -0400
parents e1e7acef8eab
children
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1 #ifndef LCSMETRIC_H_
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2 #define LCSMETRIC_H_
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3
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4 #include "Metric.h"
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5
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6 /**
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7 * LCSMetric class.
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8 *
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9 * The Longest Common Subsequence metric
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10 * This class mesures :
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11 * 1) the similarity (number of points in "common", ie relative to distance similarity threshold) ;
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12 * 2) the normalized distance between two trajectories
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13 */
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14
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15 template<typename Tr, typename To>
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16 class LCSMetric: public Metric<Tr, To>
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17 {
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18 public:
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19 /**
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20 * Constructor.
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21 */
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22 LCSMetric() : similarityThreshold(0.0), eps(1e-6)
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23 {
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24 }
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25
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26 /**
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27 * Set similarity threshold between two points.
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28 *
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29 * @param[in] similarityThreshold similarity threshold
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30 */
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31 bool setSimilarityThreshold(double similarityThreshold)
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32 {
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33 if (similarityThreshold >= 0.0)
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34 {
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35 this->similarityThreshold = similarityThreshold;
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36 return true;
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37 }
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38 return false;
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39 }
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40
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41 /**
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42 * Set machine epsilon.
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43 *
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44 * @param[in] eps machine epsilon
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45 */
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46 bool setEps(double eps)
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47 {
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48 if (eps >= 0.0)
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49 {
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50 this->eps = eps;
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51 return true;
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52 }
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53 return false;
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54 }
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55
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56 /**
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57 * Compute similarity between two trajectories.
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58 *
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59 * @param[in] a input trajectory
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60 * @param[in] b input trajectory
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61 * @param[out] result distance between two trajectories
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62 */
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63 void distance(const Trajectory<Tr> *a, const Trajectory<Tr> *b, To &result, unsigned int nbOfPoints = std::numeric_limits<unsigned int>::max())
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64 {
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65 result = To(0);
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66 unsigned int LCSS = 0;
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67 similarity(a,b, LCSS);
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68 unsigned int min_size = min(a->size(),b->size());
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69 result = 1 - double(LCSS/min_size);
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70 }
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71
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72 /**
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73 * Compute similarity between two trajectories.
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74 *
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75 * @param[in] a input trajectory
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76 * @param[in] b input trajectory
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77 * @param[out] result similarity between two trajectories
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78 */
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79 void similarity(const Trajectory<Tr> *a, const Trajectory<Tr> *b, unsigned int &result)
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80 {
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81 unsigned int LCS[a->size() + 1][b->size() + 1];
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82
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83 { //initialisation
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84 for (unsigned int i = 0; i <= a->size(); ++i)
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85 {
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86 LCS[i][0] = 0;
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87 }
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88
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89 for (unsigned int j = 0; j <= b->size(); ++j)
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90 {
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91 LCS[0][j] = 0;
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92 }
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93 }
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94
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95 { //algorithm
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96 for (unsigned int i = 1; i <= a->size(); ++i)
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97 {
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98 for (unsigned int j = 1; j <= b->size(); ++j)
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99 {
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100 cv::Point3_<typeof(static_cast<Tr>(a->getPoint(i-1)).x)> p(a->getPoint(i - 1) - b->getPoint(j - 1));
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101 double distance = sqrt(pow(p.x, 2) + pow(p.y, 2) + pow(p.z, 2)); // il faudrait généraliser
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102 if (distance <= similarityThreshold + eps)
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103 { //a[i] == b[j]
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104 LCS[i][j] = LCS[i - 1][j - 1] + 1;
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105 }
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106 else
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107 {
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108 LCS[i][j] = std::max(LCS[i - 1][j], LCS[i][j - 1]);
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109 }
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110 }
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111 }
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112 }
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113
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114 result = LCS[a->size()][b->size()];
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115 }
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116
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117 private:
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118 /**
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119 * Similarity threshold between two points.
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120 */
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121 double similarityThreshold;
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122
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123 /**
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124 * Machine epsilon.
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125 */
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126 double eps;
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127
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128 };
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129
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130 #endif /* LCSMETRIC_H_ */