Proceedings ArticleDOI
Age classification from facial images
Young Ho Kwon,da Vitoria Lobo +1 more
- pp 762-767
TLDR
This is the first reported work to classify age, and to successfully extract and use natural wrinkles, from facial images, based on cranio-facial changes in feature-position ratios, and on skin wrinkle analysis.Abstract:
The ability to classify age from a facial image has not been pursued in computer vision. This research addresses the limited task of age classification of a facial image into a baby, young adult, and senior adult. This is the first reported work to classify age, and to successfully extract and use natural wrinkles. We present a theory and practical computations for visual age classification from facial images, based on cranio-facial changes in feature-position ratios, and on skin wrinkle analysis. Three age groups are classified. >read more
Citations
More filters
Journal ArticleDOI
Recognizing action units for facial expression analysis
TL;DR: An Automatic Face Analysis (AFA) system to analyze facial expressions based on both permanent facial features and transient facial features in a nearly frontal-view face image sequence and Multistate face and facial component models are proposed for tracking and modeling the various facial features.
Proceedings ArticleDOI
Age and gender classification using convolutional neural networks
Gil Levi,Tal Hassncer +1 more
TL;DR: This paper proposes a simple convolutional net architecture that can be used even when the amount of learning data is limited and shows that by learning representations through the use of deep-convolutional neural networks, a significant increase in performance can be obtained on these tasks.
Journal ArticleDOI
Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks
TL;DR: A deep learning solution to age estimation from a single face image without the use of facial landmarks is proposed and the IMDB-WIKI dataset is introduced, the largest public dataset of face images with age and gender labels.
Journal ArticleDOI
Age Synthesis and Estimation via Faces: A Survey
TL;DR: The complete state-of-the-art techniques in the face image-based age synthesis and estimation topics are surveyed, including existing models, popular algorithms, system performances, technical difficulties, popular face aging databases, evaluation protocols, and promising future directions are provided.
Journal ArticleDOI
Age and Gender Estimation of Unfiltered Faces
TL;DR: This paper presents a robust face alignment technique, which explicitly considers the uncertainties of facial feature detectors, and describes the dropout-support vector machine approach used by the system for face attribute estimation, in order to avoid over-fitting.
References
More filters
Journal ArticleDOI
Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Proceedings ArticleDOI
Face recognition using eigenfaces
Matthew Turk,Alex Pentland +1 more
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
Application of the Karhunen-Loeve procedure for the characterization of human faces
Michael Kirby,Lawrence Sirovich +1 more
TL;DR: The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion, which results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix.
Journal ArticleDOI
Face recognition: features versus templates
Roberto Brunelli,Tomaso Poggio +1 more
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.