Facial image processing

[No abstract available

Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment

Obstructive sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). OSA is generally diagnosed through a costly procedure requiring an overnight stay of the patient at the hospital. This has led to proposing less costly procedures based on the analysis of patients' facial images and voice recordings to help in OSA detection and severity assessment. In this paper we investigate the use of both image and speech processing to estimate the apnea-hypopnea index, AHI (which describes the severity of the condition), over a population of 285 male Spanish subjects suspected to suffer from OSA and referred to a Sleep Disorders Unit. Photographs and voice recordings were collected in a supervised but not highly controlled way trying to test a scenario close to an OSA assessment application running on a mobile device (i.e., smartphones or tablets). Spectral information in speech utterances is modeled by a state-of-the-art low-dimensional acoustic representation, called i-vector. A set of local craniofacial features related to OSA are extracted from images after detecting facial landmarks using Active Appearance Models (AAMs). Support vector regression (SVR) is applied on facial features and i-vectors to estimate the AHI.The activities in this paper were funded by the Spanish Ministry of Economy and Competitiveness and the European Union (FEDER) as part of the TEC2012-37585-C02 (CMC-V2) project. Authors also thank Sonia Martinez Diaz for her effort in collecting the OSA database that is used in this study

Data protection and privacy issues concerning facial image processing in public spaces

The European Council has concluded in October 2013 that “It is important to foster the trust of citizens and businesses in the digital economy. The timely adoption of a strong EU General Data Protection framework and the Cyber-Security Directive is essential for the completion of the Digital Single Market by 2015.” This paper discusses the collection and processing of personal data in the context of the EU-funded ADMOS project whose aim is to detect in real time whether or not a person has noticed an advert and, if so, their profile in terms of gender and age. We review the issues and current legislation on the processing of personal data in the context of information systems, and how the project has incorporated a solution that fully satisfies current and proposed legislation on data protection

Reconstruction of Images from Gabor Graphs with Applications in Facial Image Processing

Graphs labeled with complex-valued Gabor jets are one of the important data formats for face recognition and the classification of facial images into medically relevant classes like genetic syndromes. We here present an interpolation rule and an iterative algorithm for the reconstruction of images from these graphs. This is especially important if graphs have been manipulated for information processing. One such manipulation is averaging the graphs of a single syndrome, another one building a composite face from the features of various individuals. In reconstructions of averaged graphs of genetic syndromes, the patients' identities are suppressed, while the properties of the syndromes are emphasized. These reconstructions from average graphs have a much better quality than averaged images

Diagnostic Decision Support System in Genetic Diseases: The FaceGP DDSS

A great number of genetic disorders indicating a characteristic pattern of facial anomalies can be typically identified by analysing specific features with the aid of facial image processing methods. This study proposes a novel computer-assisted and cost-effective method by merging several methods in the characterization of the facial dysmorphology, in particular a method relying primary on face image capture and manipulation to diagnose genetic diseases