Thermal Infrared Imaging-Based Affective Computing and Its Application to Facilitate Human Robot Interaction: A Review

Abstract

Over recent years, robots are increasingly being employed in several aspects of modern society. Among others, social robots have the potential to benefit education, healthcare, and tourism. To achieve this purpose, robots should be able to engage humans, recognize users’ emotions, and to some extent properly react and "behave" in a natural interaction. Most robotics applications primarily use visual information for emotion recognition, which is often based on facial expressions. However, the display of emotional states through facial expression is inherently a voluntary controlled process that is typical of human–human interaction. In fact, humans have not yet learned to use this channel when communicating with a robotic technology. Hence, there is an urgent need to exploit emotion information channels not directly controlled by humans, such as those that can be ascribed to physiological modulations. Thermal infrared imaging-based affective computing has the potential to be the solution to such an issue. It is a validated technology that allows the non-obtrusive monitoring of physiological parameters and from which it might be possible to infer affective states. This review is aimed to outline the advantages and the current research challenges of thermal imaging-based affective computing for human–robot interaction.

ET-CycleGAN: Generating Thermal Images from Images in the Visible Spectrum for Facial Emotion Recognition

“…In the last few years, thermal imaging has attracted the attention of the community in affective computing due to its potential use in certain conditions [7]. Due to the small size of thermal datasets, most of the works in the literature used hand-crafted features to train a classifier.…”

Smart Sensor Based on Biofeedback to Measure Child Relaxation in Out-of-Home Care

“…These investigations have used physiological signals measured with contact sensors [ 10 , 11 , 12 , 13 , 14 , 15 ]. Additional studies have been carried out to detect emotions using infrared thermography [ 16 , 17 , 18 , 19 ]. These studies have generated great interest due to the fact that this technology is non-invasive, cost effective, and insensitive to lighting [ 20 ].…”

Automated convolutional neural network approach for discriminating systemic sclerosis on the basis of hand thermal pattern

“…Thermal IR imaging is a well-known and widely used imaging technique that enables contactless assessment of the skin thermal distribution [17][18][19]. Capturing the infrared radiation spontaneously emitted by the body, the thermal camera is able to convert it into a digital map of the body superficial temperature profile [20,21]. The technique has become an important tool in medical research, thanks to its contactless, non-invasive, and security features [22,23].…”