Uses information from the user and from the tracker to update the positive and negative target model for both ferns and templates.
Method SummaryModifier and TypeMethodDescription
voidSelect positive and negative examples based on the region the user's initially selected region.
protected voidMark regions which were local maximums and had high confidence as negative.
voidUpdates learning using the latest tracking results.
initialLearningSelect positive and negative examples based on the region the user's initially selected region. The selected region is used as a positive example while all the other regions far away are used as negative examples.
targetRegion- user selected region
cascadeRegions- Set of regions used by the cascade detector
updateLearningpublic void updateLearning
(Rectangle2D_F64 targetRegion)Updates learning using the latest tracking results.
targetRegion- Region selected by the fused tracking
learnAmbiguousNegativeprotected void learnAmbiguousNegative
(Rectangle2D_F64 targetRegion)Mark regions which were local maximums and had high confidence as negative. These regions were candidates for the tracker but were not selected