- a -

• alpha : BoostableClassifier< WeakClassifier > , svm_train< Functor >
• auto_negative : datasetitem

- b -

• bias : svm_train< Functor >
• bin : PrecomputedPatternResponse< ResponseType >
• bin_size : BayesianStump< DataType >
• box : Candidate
• bpp : ImageHandle

- c -

• C : svm_train< Functor >
• category : Candidate , datasetobject , DecisionTree< T, DataType > , detail::CandidateParam , IndirectDecisionTree< DataType > , ObjectDetectorParams , Pattern< Descriptor > , PrecomputedPatternResponse< ResponseType > , WeightedPatternResponse< ResponseType >
• channel : IntegralChannelFeature
• cl_geom : detail::CandidateParam
• classifier : DecisionTree< T, DataType > , IndirectDecisionTree< DataType >
• concurrent_jobs : ObjectDetectorGlobalParams

- d -

• d : BinaryWeightedPatternResponse< ResponseType > , WeightedPattern< Descriptor > , WeightedPatternResponse< ResponseType >
• data : ImageHandle , IntegralImageHandle< T >
• default_pattern : BaseHaarFeatureGenerator
• depth : DecisionTreeLearner< Aggregator >
• desc_size : HoGParams
• downsampling : BootStrapParams , ObjectDetectorParams

- e -

• enabled : ObjectDetectorParams
• epsilon : svm_train< Functor >

- f -

• feature_index : IndirectBinaryClassifier< Policy >
• filename : datasetitem
• flags : Candidate

- g -

• grouped : Candidate

- h -

• height : detail::LocalMaxima< D, FeatureListType, Param >

- i -

• id : detail::LocalMaxima< D, FeatureListType, Param >

- l -

• left : DecisionTree< T, DataType > , IndirectDecisionTree< DataType >

- m -

• m : svm_train< Functor >
• m_border : BaseIntegralChannelFeatureGenerator
• m_classifier : HardCascadeStage< WeakClassifier >
• m_classifs : ObjectDetectorWrapperBase< _Preprocessor, _Instance >
• m_clsparams : ObjectDetectorWrapperBase< _Preprocessor, _Instance >
• m_featRange : BayesianStump< DataType >
• m_feats : BaseHaarFeatureGenerator
• m_minFeatArea : BaseHaarFeatureGenerator , BaseIntegralChannelFeatureGenerator
• m_minFeatValue : BayesianStump< DataType >
• m_minWidth : BaseHaarFeatureGenerator , BaseIntegralChannelFeatureGenerator
• m_mw : BaseHaarFeatureGenerator , BaseIntegralChannelFeatureGenerator
• m_nchannel : BaseIntegralChannelFeatureGenerator
• m_searchRoi : ObjectDetectorParams
• m_src : detail::LocalMaxima< D, FeatureListType, Param >
• m_srcSearchRanges : ObjectDetectorParams
• m_step : BaseHaarFeatureGenerator , BaseIntegralChannelFeatureGenerator
• m_truthTable : BayesianStump< DataType >
• m_weak_classifiers : SoftCascadeClassifier< T >

- n -

• n : detail::LocalMaxima< D, FeatureListType, Param > , svm_train< Functor >
• n_bases : StoredFeatureGenerator< TFeature >
• n_cells_per_block : HoGPreprocessor
• n_features : PrecomputedPatternResponse< ResponseType >
• n_pattern : MultiClassDataSetHandle< _PatternType, DataParams >
• n_patternP : DataSetHandle< Aggregator >
• n_samples : PrecomputedPatternResponse< ResponseType >
• negative_random_samples : BootStrapParams
• nms_step : BootStrapParams
• nScales : ObjectDetectorGlobalParams
• number_of_bins : PrecomputedPatternResponse< ResponseType >

- o -

• object : datasetitem
• octave_mode : ObjectDetectorGlobalParams
• offset : CollapsedHaarNode

- p -

• parity : DecisionStump< DataType >
• pr : RealDecisionStump< DataType >

- r -

• rejection : HardCascadeStage< WeakClassifier > , SoftCascadeStage< WeakClassifier >
• response : Candidate , PrecomputedPatternResponse< ResponseType >
• response_range : PrecomputedPatternResponse< ResponseType >
• responses : MultiClassDecisionStumpMultiThreshold< DataType > , MultiClassDecisionStumpSingleThreshold< DataType >
• roi : datasetobject

- s -

• scale : Candidate , detail::CandidateParam
• scale_factor : BootStrapParams
• sign : CollapsedHaarNode
• step : detail::CandidateParam
• step_mode : ObjectDetectorParams
• stride : detail::LocalMaxima< D, FeatureListType, Param > , ImageHandle
• sz : datasetitem , ObjectDetectorParams

- t -

• templates : DataSetHandle< Aggregator > , MultiClassDataSetHandle< _PatternType, DataParams >
• test : WeightedPattern< Descriptor >
• th : DecisionStump< DataType > , DecisionTree< T, DataType > , IndirectDecisionTree< DataType > , MultiClassDecisionStumpSingleThreshold< DataType > , ObjectDetectorParams , RealDecisionStump< DataType > , SimpleDecisionStump< DataType >
• thMin : BootStrapParams
• thn : AbsDecisionStump< DataType >
• threshold : detail::LocalMaxima< D, FeatureListType, Param >
• tol : svm_train< Functor >
• Type : AbsDecisionStump< DataType > , BayesianStump< DataType > , BinaryClassifier< FeatureExtractor, Policy > , BoostableClassifier< WeakClassifier > , DecisionStump< DataType > , DecisionTree< T, DataType > , IndirectBinaryClassifier< Policy > , MultiClassClassifier< FeatureExtractor, MultiClassPolicy > , NaiveDecisionStump , RealDecisionStump< DataType > , SimpleDecisionStump< DataType >

- v -

• value : BinaryWeightedPatternResponse< ResponseType > , WeightedPatternResponse< ResponseType >

- w -

• w : svm_train< Functor >
• weight : datasetobject , Pattern< Descriptor >
• weights : PrecomputedPatternResponse< ResponseType >
• width : detail::LocalMaxima< D, FeatureListType, Param > , ImageHandle , IntegralImageHandle< T > , IntegralImageParams , MultiClassDataSetHandle< _PatternType, DataParams > , NormalizedHaarFeature

- x -

• x : svm_train< Functor >
• x0 : IntegralChannelFeature , SumAreaFeature

- y -

• y : svm_train< Functor >
• yr : Candidate