Tutorial Half Day Session – Afternoon
Emotional Intelligence for Cognitive Robotics

Mode: Online/Offline

Abstract: Humans are considered to be nature's best creation. What takes humans at an advantageous rank as compared to other living beings is possibly intelligence and cognitive abilities. With the advancement of technology especially Deep Neural Network (DNN) we are even succeeding in imparting intelligence in robots. Though robots can ease human life by performing different intelligent activities, they still lack human emotions. The objective of Artificial Emotional Intelligence field is to give computers/robots abilities so that they can not only understand its user's emotions but also can interact in an emotional manner. Artificial Emotional Intelligence (AEI) is one step forward in making robots more human-like. The field of AEI sits at the juncture of Computer Vision, Machine Learning especially DNN and Natural Language Processing.

Learning Objective: This tutorial focuses on the visual channel of AEI. Specifically, we shall learn about the following.

  • Different parts of AEI: recognition, synthesis, interaction
  • Different ways of representation of emotional space: e.g., six basic emotions, FACS, valence-arousal space
  • Different types of emotional expressions: artificial/fake, spontaneous, micro expressions (uncontrollable real emotions actually felt by persons and can be used for deception/fraud detection) and ways to detect/differentiate them
  • Datasets
  • Discussion about how AEI is utilized in Cognitive Robotics
  • Case studies on the most advanced technology with algorithms, implementation details, ablation, drawbacks and advantages.

Expected Length of the Tutorial: 2:30 hrs

Maximum Number of Attendees Participating: No limit

Intended Audience and Level: The tutorial aims for researchers who are conversant with Computer Vision and Machine Learning (including DNN) and may or may not have much understanding of AEI. It will also be beneficial for those who are interested in advanced technology related to CV or DNN.

Tutorial Speaker: Dr.Swapna Agarwal, TCS Research, Kolkata

Short Bio:

Dr.Swapna Agarwal is a scientist working with the Cognitive Robotics Research group, TCS Research. She has done PhD in Affective Computing from the esteemed Indian Statistical Institute. She was a university topper in her student years. Her research interests include Emotional Intelligence, Machine Learning including Deep Neural Networks and Computer Vision. She has won multiple national and international awards in these fields including Young IT Professional Award, Special Mention Award at NCVPRIPG, felicitation from Google for Continued Contribution in Computer Science, two times finalist at Google India Women in Engineering Award. She is in the Board of Studies for Bachelors and Masters degrees in multiple institutes and she serves as program committee member/reviewer of several esteemed international conferences and journals including WACV, ICVGIP, ICIP, TIP, TMM. She has published several research papers in high impact factor journals and Core A* ranked conferences. She also has several granted national and international patents to her credit. More information may be found by accessing below weblinks: