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1、IROS2012VilaMoura,Algarve,PortugalPCL::MachineLearning–TreesandFernsStefanHolzer,TUMunich(TUM)October13,2012OverviewGoalfortoday:MachineLearninginPCL-IntroductiontoDecisionTreesandFerns-Howto:LearnanduseDecisionTrees-Howto:LearnanduseFernsMotivationComputingfeaturesfromorganizeddataisco
2、mputationallyexpensive!estimatingcurvatureRGBimagedetectingkeypointsdepthmapfindingobjectpartsetc…matchingkeypointsetc…Trees/Ferns:?Basedonsimpleandfastcomparisons?Canbeeasilyparallized(e.g.onGPUs)PCL-MLPCL-ML:PCL′sMachineLearningLibrary–DecisionTrees?Asksadifferentquestionateachnode–Fe
3、rnsClassifier?Asksabunchofquestions.atthesametime.....PCL-ML:DecisionTreesToy-Example:CurvatureEstimationWhatdoweneed??TrainingData?Tree-LearningProcedure?Tree-EvaluationProcedurePCL-ML:DecisionTreesCreatingTrainingData:RecordPointCloudsComputeCurvaturesTrainDecisionTreeusingKinectPCL-M
4、L:DecisionTreesBasicStructureofaDecisionTree:root-node?Treestartswitharoot-nodePCL-ML:DecisionTreesBasicStructureofaDecisionTree:???Treestartswitharoot-node?Decisionsbasedondepthcomparisonsxx12x1israndompositionx2israndompositionNxNwindowPCL-ML:DecisionTreesBasicStructureofaDecisionTree
5、:???Treestartswitharoot-node?Decisionsbasedondepthcomparisons?Thresholdisappliedondepthdifferencetomakedecisionxx12x1israndompositionx2israndompositionNxNwindowPCL-ML:DecisionTreesBasicStructureofaDecisionTree:???Treestartswitharoot-node?Decisionsbasedondepthcomparisons?Thresholdisappli
6、edondepthdifferencetomakedecision?x,xandthresholdareselectedduringtraining12xx12x1israndompositionx2israndompositionNxNwindowPCL-ML:DecisionTreesBasicStructureofaDecisionTree:?Treestartswitharoot-node?Decisionsbasedondepthcomparisons?Thresholdisappliedondepthdifferencetomakedecision?x,x
7、andthresholdareselectedduringtraining12?Decisionsaretrackeddowntillleafleafxx12x1israndompositionx2israndompositionNxNwindowPCL-ML:DecisionTreesBasicStructureofaDecisionTree:?Treestartswitharoot-node?Decisionsbasedondepthcomparisons?Thresholdisappliedondepthdifferencetomakedeci
