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In this paper, we propose a face detection framework that combines both feature, and skin pixel approaches, while making the framework self adaptive which is important for non controlled environmental conditions. The framework uses skin color information to reduce the search space for faces by localizing the probable skin regions using a mixture of multivariate Gaussians whose parameters are first...
This paper describes a new eigenface based face detection using boosted eigen features. Eigenfaces have long been used for face detection and recognition. The basic detection and recognition system works by projecting the face images onto a feature space that spans significant variations among the training set. But the distance from the face space is not a reliable measure to classify faces from non-faces...
Current object detection systems reach high detection rates, at the expense of requiring a large training database. This paper presents a new method for object detection, that gives state-of-the-art results, while using a reduced training database. The proposed system relies on a new local feature extraction approach inspired by Convolutional Neural Networks, Principal Component Analysis and Multilayer...
This study proposes a real-time lip-reading method in smart phone environment. In smart-phone environment where the resources are limited compared to existing PC environment, it is hard to operate lip-reading in real-time. To solve this problem, this study proposes the lip area detection method and feature extraction method suitable for smart-phone environment. First, to find the accurate lip area,...
In this paper, a new algorithm of face detection based on differential images and PCA in color image is proposed which modified the eigenface technique. First, skin picking-up is carried out by color analysis of an image. Then, for finding the exact positions of faces, a finer matching is performed by eigenface in these detected fields and a mosaic template is used to suppress the false face. Considering...
In this paper, a secure face recognition system is presented, in which face detection is performed with skin color detection followed by light normalization and normalized cross correlation. Principal component analysis (PCA) is used for face verification. Due to the rising concern about the security and privacy of the biometric system, we offer a secure storage for user records by encrypting them...
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