Face Detection Using Discrete Gabor Jets And Color Information
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Object tracking and detection over a wide range of viewpoints is a long-standing problem in Computer Vision. Despite significant advance in wide-baseline sparse interest point matching and development of robust dense feature models, it remains a largely op ...
Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...
Face detection is the first step in many visual processing systems like face recognition, emotion recognition and lip reading. In this paper, we propose a novel feature called Haar Local Binary Pattern (HLBP) feature for fast and reliable face detection, p ...
This paper discusses the use of ferns (a set of binary features) for face detection. The binary feature used here is the sign of pixel intensity difference. Ferns were first introduced for keypoint recognition and showed good performance, and improving the ...
This thesis proposes a novel unified boosting framework. We apply this framework to the several face processing tasks, face detection, facial feature localisation, and pose classification, and use the same boosting algorithm and the same pool of features ( ...
In this paper, we use a hill-climbing attack algorithm based on Bayesian adaption to test the vulnerability of two face recognition systems to indirect attacks. The attacking technique uses the scores provided by the matcher to adapt a global distribution ...
Face detection allows to recognize and detect human faces and provides information about their location in a given image. Many applications such as biometrics, face recognition, and video surveillance employ face detection as one of their main modules. The ...
Detecting faces in images is a key step in numerous computer vision applications, such as face recognition or facial expression analysis. Automatic face detection is a difficult task because of the large face intra-class variability which is due to the imp ...
In multiple testing, a variety of control metrics of false positives have been introduced such as the Per Family Error Rate (PFER), Family-Wise Error Rate (FWER), the False Discovery Rate (FDR), the False Exceedence Rate (FER). In this talk, we present a c ...
Face detection is the first step in many visual processing systems like face recognition, emotion recognition and lip reading. In this paper, we propose a novel feature called Haar Local Binary Pattern (HLBP) feature for fast and reliable face detection, p ...
