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Bio

I'm a Postdoctoral Researcher at Robotics Institute , Carnegie Mellon University. I am working on facial expression analysis with Jeffrey Cohn. I was previously a Postdoctoral Researcher at Affect Analysis Group, University of Pittsburgh and a visiting Ph.D. student at Pattern Recognition and Bioinformatics Group, Delft University of Technology. I received my B.Sc., M.Sc. and Ph.D. degrees from Computer Engineering Department at Middle East Technical University, where my supervisor was Fatos Yarman Vural.

News

  • 08/2019 - Code for AFAR is released.
  • 07/2019 - Paper accepted to appear in BMVC 2019: "PAttNet: Patch-attentive deep network for action unit detection".
  • 07/2019 - Paper accepted to appear in BMVC 2019: "Unmasking the devil in the details: What works for deep facial action coding ?".
  • 06/2019 - Paper accepted to appear in ACII 2019: "FACS3D-Net: 3D convolution based spatiotemporal representation for action unit detection".
  • 03/2019 - Demo paper accepted to appear in FG 2019: "AFAR: A deep learning based tool for automated facial affect recognition".
  • 01/2019 - Paper accepted to appear in FG 2019: "Cross-domain AU detection: domains, learning approaches, and measures".
  • 12/2018 - Paper accepted to appear in Brain Imaging and Behavior: "Gender Classification using Mesh Networks on Multiresolution Multitask fMRI Data".
  • 11/2018 - Book chapter to appear in Multimodal behavioral analysis in the wild: Advances and Challenges: "Affective facial computing: Generalizability across domains".
  • 09/2018 - Paper accepted to appear in Image and Vision Computing: "Modeling and Synthesis of Kinship Patterns of Facial Expressions".

Research Interests

  • Affective Computing
  • Facial expression analysis
  • Biomedical signal processing

Publications

  • I. Onal Ertugrul, L. A. Jeni, J. F. Cohn, PAttNet: Patch-attentive deep network for action unit detection. British Machine Vision Conference (BMVC), 2019.
  • K. Niinuma, L. A. Jeni, I. Onal Ertugrul, J. F. Cohn, Unmasking the devil in the details: What works for deep facial ation coding ? British Machine Vision Conference (BMVC), 2019.
  • L. Yang, I. Onal Ertugrul, J. F. Cohn, Z. Hammal, D. Jiang, H. Sahli, FACS3D-Net: 3D convolution based spatiotemporal representation for action unit detection. International Conference on Affective Computing and Interactive Intelligence (ACII), 2019 (Oral presentation).
  • I. Onal Ertugrul, J. F. Cohn, L. A. Jeni, Z. Zhang, L. Yin, Q. Ji, Cross-domain AU detection: domains, learning approaches and measures. IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2019 (Oral presentation).
  • I. Onal Ertugrul, L. A. Jeni, W. Ding, J. F. Cohn, AFAR: A deep learning based tool for automated facial affect recognition. IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2019.
  • I. Onal Ertugrul, M. Ozay, F. Yarman Vural, Gender Classification using Mesh Networks on Multiresolution Multitask fMRI Data, Brain Imaging and Behavior, 2018.
  • J. F. Cohn, I. Onal Ertugrul, W-S. Chu, J. M. Girard, L. A. Jeni, Z. Hammal, Affective Facial Computing: Generalizability Across Domains In Multi-modal Behavioral Analysis in the Wild: Advances and Challenges, 2018.
  • I. Onal Ertugrul, L. A. Jeni, H. Dibeklioglu, Modeling and Synthesis of Kinship Patterns of Facial Expressions Image and Vision Computing, 2018.
  • J. F. Cohn, L. A. Jeni, I. Onal Ertugrul, D. Malone, M. Okun, D. Borton, W. Goodman, Automated Multimodal Measurement of Behavioral Response to Deep Brain Stimulation in Obsessive-Compulsive Disorder: A Pilot Study ICMI, 2018.
  • B. B. Kivilcim, I. Onal Ertugrul, F. Yarman Vural, Modeling Brain Networks with Artificial Neural Networks, Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-imaging Modalities , 2018.
  • I. Onal Ertugrul, M. Ozay, F. Yarman Vural, Encoding the Local Connectivity Patterns of fMRI for Cognitive Task and State Classification, Brain Imaging and Behavior, 2018.
  • I. Onal Ertugrul, L. A. Jeni, J. F. Cohn, FACSCaps: Pose-Independent Facial Action Coding with Capsules, IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
  • I. Onal Ertugrul, M. Ozay, F. T. Yarman Vural, Hierarchical Multi-resolution Mesh Networks for brain decoding, Brain Imaging and Behavior, 2017, https://doi.org/10.1007/s11682-017-9774-z [link] [bibtex]
  • I. Onal Ertugrul, H. Dibeklioglu, What will your future child look like? Modeling and Synthesis of Hereditary Patterns of Facial Dynamics, IEEE International Conference on Automatic Face and Gesture Recognition (FG), 2017. (Oral presentation) [link] [bibtex]
  • I. Onal, M. Ozay, E. Mizrak, I. Oztekin, F. T. Yarman Vural, A New Representation of fMRI Signal by a Set of Local Meshes for Brain Decoding, IEEE Transactions on Signal and Information Processing over Networks (T-SIPN), 2017. [link] [bibtex]
  • A. M. Ertugrul, I. Onal, C. Acarturk, Does the Strength of Sentiment Matter? A Regression Based Approach on Turkish Social Media, International Conference on Applications of Natural Language to Information Systems (NLDB), 2017. [link] [bibtex]
  • A. Afrasiyabi, I. Onal Ertugrul, F. T. Yarman Vural, A Sparse Temporal Mesh Model for Brain Decoding, 15th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC), 2016. [link] [bibtex]
  • I. Onal, M. Ozay, F. T. Yarman Vural, Functional Mesh Model with Temporal Measurements for Brain Decoding, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015. [link] [bibtex]
  • I. Onal, M. Ozay, F. T. Yarman Vural, Modeling Voxel Connectivity for Brain Decoding, International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2015. [link] [bibtex]
  • I. Onal, A. Temizel, F. T. Yarman Vural, Spatial and Temporal Feature Extraction for Brain Decoding using CUDA, GPU Technology Conference (GTC), 2015. [link]
  • I. Onal, E. Aksan, B. Velioglu, O. Firat, M. Ozay, I. Oztekin, F. T. Yarman Vural, A Brain Network for Cognitive State Analysis IEEE 23rd Conference on Signal Processing and Communications Applications (SIU), 2015. (in Turkish) [link] [bibtex]
  • O. Firat, M. Ozay, I. Onal, I. Oztekin, F. T. Yarman Vural, Enhancing Local Linear Models Using Functional Connectivity for Brain State Decoding, International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2013. [link] [bibtex]
  • I. Onal, E. Aksan, B. Velioglu, O. Firat, M. Ozay, I. Oztekin, F. T. Yarman Vural, Modeling the Brain Connectivity for Pattern Analysis, 22nd International Conference on Pattern Recognition (ICPR), 2014. [link] [bibtex]
  • O. Firat, I. Onal, E. Aksan, B. Velioglu, I. Oztekin, F. T. Yarman Vural, Large Scale Functional Connectivity For Brain Decoding, 11th IASTED International Conference on Biomedical Engineering (BioMed), 2014. [pdf] [bibtex]
  • B. Velioglu, E. Aksan, I. Onal, O. Firat, M. Ozay, F. T. Yarman Vural, Functional Networks of Anatomic Brain Regions, 13th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC), 2014. [link] [bibtex]
  • I. Onal, A. M. Ertugrul, R. Cakici, Effect of Using Regression on Class Confidence Scores in Sentiment Analysis of Twitter Data, 5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis (WASSA), 2014. [pdf] [bibtex]
  • A. M. Ertugrul, I. Onal, RemindMe: An Enhanced Mobile Location-Based Reminder Application, International Conference on Future Internet of Things and Cloud (FiCloud), 2014. [link] [bibtex]
  • I. Onal, E. Aksan, B. Velioglu, O. Firat, M. Ozay, I. Oztekin, F. T. Yarman Vural, Estimating Brain Connectivity for Pattern Analysis, 22nd IEEE Conference on Signal Processing and Communications Applications (SIU), 2014. (in Turkish) [link] [bibtex]
  • I. Onal, A. M. Ertugrul, Effect of Using Regression in Sentiment Analysis, 22nd IEEE Conference on Signal Processing and Communications Applications (SIU), 2014. (in Turkish) [link] [bibtex]
  • A. M. Ertugrul, I. Onal, Çeşitli Konum Etiketleme Opsiyonlarıyla Zenginleştirilmiş Yeni Bir Konum Bazlı Hatırlatma Uygulaması, 8. Ulusal Yazılım Mühendisliği Sempozyumu (UYMS), 2014. (in Turkish) [pdf] [bibtex]
  • I. Onal, M. Ozay, O. Firat, I. Oztekin, F. T. Yarman Vural, An Information Theoretic Approach to Classify Cognitive States Using fMRI, 13th IEEE International Conference on BioInformatics and BioEngineering (BIBE), 2013. [link] [bibtex]
  • I. Onal, M. Ozay, O. Firat, I. Oztekin, F. T. Yarman Vural, Analyzing the Information Distribution in the fMRI measurements by estimating the degree of locality, 35th Medicine and Biology Society (EMBC), 2013. [link] [bibtex]
  • O. Firat, M. Ozay, I. Onal, I. Oztekin, F. T. Yarman Vural, Functional Mesh Learning for Pattern Analysis of Cognitive Processes, 12th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC), 2013. (Best Paper Award) [link] [bibtex]
  • O. Firat, M. Ozay, I. Onal, I. Oztekin, F. T. Yarman Vural, Representation of Cognitive Processes Using the Minimum Spanning Tree of Local Meshes, 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013. [link] [bibtex]
  • I. Önal, K. Kardas, Y. Rezaeitabar, U. Bayram, M. Bal, I. Ulusoy, N. Kesim Çiçekli, A framework for Detecting Complex Events in Surveillance Videos, 3rd IEEE International Workshop on Advances in Automated Multimedia Surveillance for Public Safety (AAMS-PS), 2013. [link] [bibtex]
  • I. Onal, M. Ozay, O. Firat, I. Oztekin, F. T. Yarman Vural, Information Distribution Analysis in the fMRI measurements with Degree of Locality Estimation, IEEE 21th Conference on Signal Processing and Communications Applications (SIU), 2013. (in Turkish) [link] [bibtex]
  • O. Firat, M. Ozay, I. Onal, I. Oztekin, F. T. Yarman Vural, Cognitive Processes Representation Using Minimum Spanning Tree of Local Meshes, IEEE 21th Conference on Signal Processing and Communications Applications (SIU), 2013. (in Turkish) [link] [bibtex]
  • O. Firat, M. Ozay, I. Onal, I. Oztekin, F. T. Yarman Vural, A Mesh Learning Approach for Brain Data Modeling, IEEE 20th Conference on Signal Processing and Communications Applications (SIU), 2012. (in Turkish) [link] [bibtex]