Human Centered Computer Vision

Presenter: Hazım Kemal Ekenel

Date and time: 7th July 2pm CEST


Facial image processing and analysis is the task of automatically analyzing face images in order to acquire information about the depicted persons. This includes a person’s identity, emotional state, facial gestures, age, and gender. The large number of European projects that involves facial image processing as a part shows its crucial role in a wide range of application domains, such as security, smart environments, human-computer interfaces, and content-based image and video analysis. Considering the advanced security needs of the society and the shift to the paradigm of human-centered computing for natural interfaces, the interest in face processing is expected to continue with increasing pace. In this talk Dr. Ekenel is going to present an overview of computer vision research activities @ Smart Interaction and Machine Intelligence (SiMiT) Lab. The covered topics will be about face alignment, face recognition, facial expression analysis, and their applications. Deep learning topics like transfer learning, dataset bias, domain adaptation, and context adaptation will also be discussed.


Dr. Ekenel is a full Professor at the Department of Computer Engineering in Istanbul Technical University in Turkey.  His research interest covers computer vision and machine learning with a focus on face analysis and human perception. He has published more than 100 peer reviewed publications in prestigious international journals, conferences, and workshops in the related fields. He received his Ph.D. degree in Computer Science from the University of Karlsruhe (TH) in 2009. He has founded the Facial Image Processing and Analysis group at the Department of Computer Science in Karlsruhe Institute of Technology. He has received the EBF European Biometric Research Award in 2008 for his contributions to the field of face recognition. He is also a recipient of the Science Academy Turkey’s Young Scientist Award 2018 and IEEE Turkey Chapter Research Award 2019.

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