IEEE Signal Processing Letters · 2014 · 79 citations · 19 references
ComputingComputer ScienceComputer VisionFeature EngineeringFace RecognitionShape AnalysisAutomatic Landmark DetectionFacial Landmark DetectionLandmark DetectionLocal Feature DetectionParallel StructureScale-invariant Feature DetectionScale-invariant MatchingStatistical Feature Extraction
In this letter, we present a random cascaded-regression copse (R-CR-C) for robust facial landmark detection. Its key innovations include a new parallel cascade structure design, and an adaptive scheme for scale-invariant shape update and local feature extraction. Evaluation on two challenging benchmarks shows the superiority of the proposed algorithm to state-of-the-art methods.
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Histograms of Oriented Gradients for Human Detection
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Active Shape Models-Their Training and Application
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