Measuring the Performance of Face Localization Systems
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This paper addresses the problem of locating facial features in images of frontal faces taken under different lighting conditions. The well-known Active Shape Model method proposed by Cootes {\it et al.} is extended to improve its robustness to illuminatio ...
Statistical pattern recognition occupies a central place in the general context of machine learning techniques, as it provides the theoretical insights and the practical means for solving a variety of problems ranging from character recognition to face rec ...
In this report, we address the problem of face verification across illumination, since it has been identified as one of the major factor degrading the performance of face recognition systems. First, a brief overview of face recognition together with its ma ...
This report addresses the problem of locating facial features in images of frontal faces taken under different lighting conditions. The well-known Active Shape Model method proposed by Cootes {\it et al.} is extended in order to improve its robustness to i ...
Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authentication. The purpose of this paper is to show that the error made during the locali ...
In much of the literature devoted to face recognition, experiments are performed with controlled images (e.g. manual face localization, controlled lighting, background and pose); however, a practical recognition system has to be robust to more challenging ...
It has been previously demonstrated that systems based on local features and relatively complex statistical models, namely 1D Hidden Markov Models (HMMs) and pseudo-2D HMMs, are suitable for face recognition. Recently, a simpler statistical model, namely t ...
This thesis proposes a robust Automatic Face Verification (AFV) system using Local Binary Patterns (LBP). AFV is mainly composed of two modules: Face Detection (FD) and Face Verification (FV). The purpose of FD is to determine whether there are any face in ...
Detecting faces in images is a key step in numerous computer vision applications as face recognition for example. Face detection is a difficult task in image analysis because of the large face intra-class variability which is due to the important influence ...
Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authentication. The purpose of this paper is to show that the error made during the locali ...
