Hamdi Dibeklioğlu

Assistant Professor in the Computer Engineering Department of Bilkent University

- Title of the talk:
Recent Developments in Deep Face Analysis

 Computer analysis of faces has been a popular research area over the last two decades due to its challenging and multidisciplinary nature. Nowadays, with the pervasive presence of cameras and powerful processing devices, face analysis is getting involved in our lives. While prior studies mostly deal with recognizing identity, age, gender, and expression of basic emotions, following the recent dramatic improvements in the field of deep learning, scientific interest has shifted the focus to several different tasks. Furthermore, with the significant increase in the number of facial video databases, temporal analysis has become a default setup for face analysis, revealing subtle and complex patterns of facial responses. In this tutorial, I will present recent deep approaches to model such patterns for various tasks such as analyzing personality traits, recognizing preferences, assessing psychopathology, deceit detection, kinship verification, and age estimation. As well as overviewing methodological concepts, I will discuss recent findings and remaining research challenges in the area of face analysis.

- Short biography:

Hamdi Dibeklioğlu is an Assistant Professor in the Computer Engineering Department of Bilkent University as well as being a Research Affiliate with the Pattern Recognition & Bioinformatics Group of Delft University of Technology. He received the B.Sc. degree from Yeditepe University in 2006, the M.Sc. degree from Boğaziçi University in 2008, and the Ph.D. degree from the University of Amsterdam in 2014. Before joining Bilkent University, he was a Postdoctoral Researcher at Delft University of Technology, a Visiting Researcher at Carnegie Mellon University, University of Pittsburgh, and Massachusetts Institute of Technology. His research focuses on affective computing, computer vision, and pattern recognition. Dr. Dibeklioglu is a Program Committee Member for several top tier conferences in these areas. He was a Co-chair for the Netherlands Conference on Computer Vision 2015, a Local Arrangements Co-chair for the European Conference on Computer Vision 2016, a Publication Co-chair for the European Conference on Computer Vision 2018, and a Co-organizer of the eNTERFACE Workshop on Multimodal Interfaces 2019. He is a member of IEEE, ACM, and Computer Vision Foundation.

Session chairs

Rachid Jennane, University of Orleans, France (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)
Mohammed EL Hassouni, University of Mohammed V, Morocco (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)
Khalifa Djemal, University of Every Val d’Essonne, France (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)
Oge Marques, Florida Atlantic University, USA (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)

Aim & topics:

The recent advances in medical imaging have revolutionized the diagnostic of the medical images. Meanwhile, Big Data, Machine and Deep Learning are revolutionizing the way world medicine operate. With expanded storage capacity and new forms of data processing, big data and machine learning analytics are paving the way for more confident clinical decision-making and medicine research.
This special session aims at providing the most recent developments in the field of medical image analysis using big data, machine and deep learning algorithms.

The topics of this special session include (not limited to):

• Health and medical data collection
• Health and medical data analysis
• Health and medical image quality assessment and enhancement
• Recognition strategies in health and medical imaging
• Computer aided diagnostic
• E-health
• Telemedicine
• Health and medical image security and content transmission
• Health and medical applications

Authors are encouraged to submit their work by providing a paper including results, figures and references following the rules of IPTA’2019.

Call for papers

A PDF version of the call for papers can be found here.

Program IPTA 2019

• IPTA 2020 will be held in Paris! Click for more details

Session chairs

Aladine Chetouani, Assistant Professor, PRISME, University of Orleans, France
Leida Li, Professor, School of Artificial Intelligence, Xidian University, Xi'an 710071, China
Patrick Le Callet Professor, Image Perception & Interaction (IPI) LS2N, Polytech Nantes/Université de Nantes, France

Aim & topics:

In the last decades, visual quality assessment becomes a crucial step for several applications such as compression, restoration, printing, biometrics, recognition and so on. Indeed, images, video and 3D meshes are generally affected by different types of degradations that impact the performance of the treatments applied to the image. It’s thus necessary to dispose to an efficient tool that well predicts the quality of the visual content.
Three main approaches have been proposed in the literature. Full-Reference approach where the original image is exploited, No-Reference approach where only the degraded image is used and the Reduced-Reference approach where some characteristics of the original image are used. Some of them are mathematical-based, while some others are perceptual-based, structural-based or learning-based. Recently, authors are increasingly focusing on the use of deep learning (CNN, auto-encoder, etc.), since the latter demonstrated its effectiveness.
The objective of this special session is to provide an overview of this domain and some of its applications and tools.

The addressed topics in this special session are fully related to the IPTA 2019 conference with the following themes (not exhaustive list):

• Image and video quality assessment
• 3D meshes quality assessment
• Deep-based methods
• Quality for stereoscopic images and sequences
• Objective and subjective metrics
• Human Visual System inspired methods
• Perceptual metrics
• Saliency and visual attention
• Quality prediction methods
• Regression methods and quality
• Machine learning and quality
• Benchmarks for quality assessment
• Color and quality

For further information, please contact to:

Aladine Chetouani (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)
Leida Li (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)
Patrick Le Callet (Cette adresse e-mail est protégée contre les robots spammeurs. Vous devez activer le JavaScript pour la visualiser.)

Call for papers

A PDF version of the call for papers can be found here.