2012 · 34 citations · 11 references
ComputingAutomotive EngineeringComputer ScienceAuthenticationComputer VisionMachine LearningBiometric AuthenticationFace RecognitionFeature DetectionObject DetectionPattern RecognitionSecurity SystemsAdaboostBiometric Feature ExtractionClassifier FusionColor DetectionColor Image ProcessingFace Feature ExtractionPrincipal ComponentsPrior Related Knowledge
An improved face detection and recognition method based on information of skin color is proposed in this paper. Color is a powerful fundamental cue of human faces. Skin color detection is first performed on the input color image to reduce the computational complexity. Morphological operations are used and it gives a prior knowledge for face detection. Face is detected by Adaboost algorithm. AdaBoost learning is used to choose a small number of weak classifiers and to combine them into a strong classifier deciding whether an image is a face or not. Then, by using principal component analysis(PCA) algorithm, a specific face can be recognized by comparing the principal components of the current face to those of the known individuals in a facial database built in advance.
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