Unveiling Human Experience: Decoding Macro and Micro Emotional States with Neural Correlates of Emotion

Scope of the Workshop

This workshop focuses on the recognition and analysis of macro and micro expressions, providing valuable insights into human behavior and cognition. Macro expressions are overt and visible manifestations of emotions, conveyed through facial expressions, body language, and vocal cues, and are easily recognizable. Micro expressions, however, are fleeting, involuntary facial movements that reveal concealed emotions. The workshop will discuss the challenges in collecting and labeling datasets for these expressions and explore advanced analytical techniques and algorithm development for accurate detection. It will delve into technological advancements in computer vision, machine learning, and affective computing, emphasizing the integration of multimodal learning using multisensory data to enhance emotion recognition systems. Additionally, the workshop will explore the neural correlates of emotions, using methodologies like functional Magnetic Resonance Imaging (fMRI) to understand the brain regions activated during emotional experiences, thereby providing deeper insights into the cognitive processes behind these expressions. The practical applications of these advancements in fields such as human-computer interaction, virtual reality, gaming, and healthcare will also be examined.

Topics to Be Covered

  1. Human Emotion Recognition: Understanding the fundamentals of human emotion recognition and its significance.
  2. Macro and Micro Emotions: Exploring the differences between macro and micro emotions and their respective characteristics.
  3. Challenges in Dataset Creation: Identifying the difficulties in creating and labeling datasets for emotion recognition, particularly for micro expressions.
  4. Neural Correlates of Emotions: Examining the neural mechanisms underlying emotional experiences and how they are studied using techniques like fMRI.
  5. Algorithm Design and Development: Discussing the challenges and advancements in designing and developing robust algorithms for emotion recognition.
  6. Multimodal Data Integration: Exploring the integration of multisensory data in emotion recognition systems and the challenges associated with this approach.
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Organisers

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Dr. Santosh Kumar Vipparthi

IIT Ropar, Head, School of Artificial Intelligence and Data Engineering (AIDE)

Dr. Santosh Kumar Vipparthi, a senior member of IEEE, brings over 13 years of experience in both academia and industry. He is currently the head of the School of Artificial Intelligence and Data Engineering (sAIDE) at the Indian Institute of Technology Ropar (IIT Ropar), India. Before this, he held positions at the Mehta Family School of Data Science and Artificial Intelligence, Indian Institute of Technology Guwahati (IIT Guwahati). Dr. Vipparthi earned his Ph.D. and MTech degrees with honors from the Indian Institute of Technology Varanasi (IIT Varanasi), BHU, India, and a B.E. degree from Andhra University, India. His research interests include computer vision, affective computing, and deep learning, among others.

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Dr. Priyanka Jain

Scientist ‘F’ & Head, Neuro-Cognitive AI & XR Group, C-DAC Delhi

Dr. Priyanka Jain is Associate Director (Scientist ‘F’) in C-DAC, Delhi. Leading the Neuro-Cognitive AI & XR Group of organization with research-oriented personage, she derives new approaches and algorithms to extend the coverage of knowledge. She has in her account many mission-mode core-research AI projects of national importance. Currently, she is executing the projects funded by ministries under GoI. She has more than 60 publications, research and literature in Hindi & English. Her research area interests are AI, Neuro-Cognitive Computing, Brain Computer Interface, Natural Language Processing, High Performance Computing, and Quantum Computing. The application domain areas are focused towards Accessibility, Mental Health and Digital Forensic to serve the community.

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Dr. Rajkumari Reddy

NIMHANS, Banglore

Academics: She completed her M.Phil (Clinical Psychology), Ph.D (Neuropsychology) from NIMHANS and Post-Doctoral Fellowship (Cognitive and Affective Empathy: An fMRI study) in Cognitive Neuroscience – sponsored by Dept. of Science & Technology, Govt of India and Post Graduate Diploma in Child Rights Law from National Law University.

Visiting Associate Faculty - University of British Columbia, Vancouver, Canada under Dr. Lakshmi Yatham & Dr. Ivan Torres, Faculty of Medicine, Dept of Psychiatry (September 2022- August 2023) – for Neurocognition and Bipolar Disorder

Data handling

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Sample Video

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Schedule

Workshop Schedule

On 20th July, 2024
Human Emotion Recognition and Its Applications Using Deep Learning and Architecture Challenges 11:30 AM - 01:00 PM
Introduction to Neural Correlates of Emotions 02:00 PM - 03:00 PM
Multimodal Learning for Cognitive State Estimation 03:00 PM - 04:00 PM

References

[1] M. Verma, S. K. Vipparthi and G. Singh, "Deep Insights of Learning-Based Micro Expression Recognition: A Perspective on Promises, Challenges, and Research Needs," in IEEE Transactions on Cognitive and Developmental Systems, vol. 15, no. 3, pp. 1051-1069, Sept. 2023, doi: 10.1109/TCDS.2022.3226348.
[2] Qu, F., Wang, S.J., Yan, W.J., Li, H., Wu, S. and Fu, X., 2017. CAS (ME) $^ 2$: a database for spontaneous macro-expression and micro-expression spotting and recognition. IEEE Transactions on Affective Computing, 9(4), pp.424-436.
[3] ] http://centerforbodylanguage.com/freey

Contact Us

Mail: skvipparthi@iitrpr.ac.in

Mobile: +91-9549658135

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