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The experiments demonstrate the robustness of the proposed face detection and tracking scheme and the three streaming face recognition schemes with 99% accuracy of the CDHMM rule.
Face recognition: Face recognition schemes typically locate the eye region and then extract holistic features from the windows centered on various regions of interest [18, 19].
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This study presents an appearance-based face recognition scheme called the nonparametric-weighted Fisherfaces (NW-Fisherfaces).
In this study, we propose an appearance-based face recognition scheme called nonparametric-weighted Fisherfaces (NW-Fisherfaces).
Do they have the same face recognition system as Calum?
Figure 1 Architecture of a typical face recognition system.
In this article, we present an automatic face recognition system.
Erkin et al. [41] propose a privacy preserving face recognition system for the eigen-face recognition algorithm [63].
One of the most important steps in a face recognition system is face segmentation.
A traditional face recognition system includes three key stages: face image acquisition, face feature extraction, and feature classification.
Wright et al. [4] recently proposed the sparse representation based classification (SRC) scheme for face recognition which achieved impressive performance.
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