The Contribution of External Features to Face Recognition

نویسندگان

  • Àgata Lapedriza
  • David Masip
  • Jordi Vitrià
چکیده

In this paper we propose a face recognition algorithm that combines internal and external information of face images. Most of the previous works dealing with face recognition use only internal face features to classify, not considering the information located at head, chin and ears. Here we propose an adaptation of a top-down segmentation algorithm to extract external features from face images, and then we combine this information with internal features using a modification of the non parametric discriminant analysis technique. In the experimental results we show that the contribution of external features to face classification problems is clearly relevant, specially in presence of occlusions.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Face Recognition by Cognitive Discriminant Features

Face recognition is still an active pattern analysis topic. Faces have already been treated as objects or textures, but human face recognition system takes a different approach in face recognition. People refer to faces by their most discriminant features. People usually describe faces in sentences like ``She's snub-nosed'' or ``he's got long nose'' or ``he's got round eyes'' and so like. These...

متن کامل

Hybridization of Facial Features and Use of Multi Modal Information for 3D Face Recognition

Despite of achieving good performance in controlled environment, the conventional 3D face recognition systems still encounter problems in handling the large variations in lighting conditions, facial expression and head pose The humans use the hybrid approach to recognize faces and therefore in this proposed method the human face recognition ability is incorporated by combining global and local ...

متن کامل

Face Recognition using Eigenfaces , PCA and Supprot Vector Machines

This paper is based on a combination of the principal component analysis (PCA), eigenface and support vector machines. Using N-fold method and with respect to the value of N, any person’s face images are divided into two sections. As a result, vectors of training features and test features are obtain ed. Classification precision and accuracy was examined with three different types of kernel and...

متن کامل

A comprehensive experimental comparison of the aggregation techniques for face recognition

In face recognition, one of the most important problems to tackle is a large amount of data and the redundancy of information contained in facial images. There are numerous approaches attempting to reduce this redundancy. One of them is information aggregation based on the results of classifiers built on selected facial areas being the most salient regions from the point of view of classificati...

متن کامل

Improving LNMF Performance of Facial Expression Recognition via Significant Parts Extraction using Shapley Value

Nonnegative Matrix Factorization (NMF) algorithms have been utilized in a wide range of real applications. NMF is done by several researchers to its part based representation property especially in the facial expression recognition problem. It decomposes a face image into its essential parts (e.g. nose, lips, etc.) but in all previous attempts, it is neglected that all features achieved by NMF ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005