Authors:
Saïd Kharbouche
and
Michel Plu
Affiliation:
Orange Labs 2, France
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper describes a novel and efficient approach that integrates clothing similarity into face identification process in personal photos. The information extracted from people’s clothes would be helpful if they are dissimilar, however, this information could make errors and noise if we have some people with similar clothes. To resolve this problem, we propose here a better methodology that exploits clothing similarity. The main idea is summarized as follows: if a person is well identified in a detected face, instead to reinforce this person in every face (in other photo) with similar clothes, we contest her/him in every face with dissimilar clothes. The weight and the influence of the information extracted from a face in a photo to another face depend on the spatiotemporal distance between photos, the similarity degree between the clothes and the incertitude level about their real identities. We utilize belief functions theory in order to manage efficiently the imprecision and the
uncertainty. Besides, the results obtained showed off the interest of our approach.
(More)