scispace - formally typeset
Journal ArticleDOI

Face recognition

TLDR
This work designs classifiers based on the well-known fisherface method and demonstrates that the proposed method comes with better performance when compared with other template-based techniques and shows substantial insensitivity to large variation in light direction and facial expression.
About
This article is published in Pattern Recognition Letters.The article was published on 2005-05-01. It has received 679 citations till now. The article focuses on the topics: Facial recognition system & Fuzzy logic.

read more

Citations
More filters
Journal ArticleDOI

Parameter learning and applications of the inclusion-exclusion integral for data fusion and analysis

TL;DR: This paper proposes that such a representation allows us to naturally extend and adapt the fuzzy integral framework toward specific applications, and focuses on the inclusion-exclusion integral, which is a generalization of the Choquet integral.
Book ChapterDOI

Chain Code-Based Local Descriptor for Face Recognition

TL;DR: This paper proposes a new chain code-based local descriptor based on string values, which are obtained when starting from a particular point of the image and searching for extrema in a given neighborhood and memorizing a path being traversed through the consequent pixels of theimage.
Journal ArticleDOI

Multi-Level Search Space Reduction Framework for Face Image Database

TL;DR: A Multi-Level Search Space Reduction framework for large scale face image database that identifies discriminating features and groups face images sharing similar properties using feature-weighted Fuzzy C-Means approach and reduces the search space.
References
More filters
Journal ArticleDOI

Eigenfaces vs. Fisherfaces: recognition using class specific linear projection

TL;DR: A face recognition algorithm which is insensitive to large variation in lighting direction and facial expression is developed, based on Fisher's linear discriminant and produces well separated classes in a low-dimensional subspace, even under severe variations in lighting and facial expressions.
Proceedings ArticleDOI

Face recognition using eigenfaces

TL;DR: An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person by comparing characteristics of the face to those of known individuals is described.
Journal ArticleDOI

Face recognition: features versus templates

TL;DR: Two new algorithms for computer recognition of human faces, one based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second based on almost-gray-level template matching are presented.
Journal ArticleDOI

The FERET database and evaluation procedure for face-recognition algorithms

TL;DR: The FERET evaluation procedure is an independently administered test of face-recognition algorithms to allow a direct comparison between different algorithms and to assess the state of the art in face recognition.
Proceedings ArticleDOI

View-based and modular eigenspaces for face recognition

TL;DR: In this paper, a view-based multiple-observer eigenspace technique is proposed for use in face recognition under variable pose, which incorporates salient features such as the eyes, nose and mouth, in an eigen feature layer.
Related Papers (5)