Authors:
A. Bottino
1
;
M. De Simone
1
;
A. Laurentini
1
and
T. Vieira
2
Affiliations:
1
Politecnico di Torino, Italy
;
2
Politecnico di Torino and Universidade Federal de Pernambuco, Italy
Keyword(s):
Kinship verification, Support Vector Machines, Principal Component Analysis, Feature Selection Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Feature Selection and Extraction
;
ICA, PCA, CCA and other Linear Models
;
Image Understanding
;
Pattern Recognition
;
Theory and Methods
Abstract:
Human face conveys to other human beings, and potentially to computers, much information such as identity, emotional states, intentions, age and attractiveness. Among this information there are kinship clues. Face kinship signals, as well as the human capabilities of capturing them, are studied by psychologist and sociologists. In this paper we present a new research aimed at analyzing, with image processing/pattern analysis techniques, facial images for detecting objective elements of similarity between siblings. To this end, we have constructed a database of high quality pictures of pairs of siblings, shot in controlled conditions, including frontal, profile, expressionless and smiling face images. A first analysis of the database has been performed using a commercial identity recognition software. Then, for discriminating siblings, we combined eigenfaces, SVM and a feature selection algorithm, obtaining a recognition accuracy close to that of a human rating panel.