Somnath Chatterjee

Papers

Total Citations

H-Index

About

Somnath Chatterjee is a leading researcher in computer vision and affective computing, with a particular focus on thermal imaging and deep learning. His most cited work, "A deep learning model for classifying human facial expressions from infrared thermal images" (2021, 56 citations), addresses a critical challenge in emotion recognition: the limitations of visible-spectrum cameras under poor lighting or occlusion. Chatterjee pioneered the use of infrared thermal imaging (IRTI) to capture physiological cues—such as temperature changes around the eyes and mouth—that correlate with emotional states, developing a deep learning architecture that achieves robust classification of facial expressions even in challenging environments. This contribution has significant implications for human-computer interaction, security, and healthcare monitoring, where non-invasive, lighting-independent emotion detection is essential. Beyond this flagship paper, his broader work explores the intersection of thermal signal processing and neural networks, advancing the reliability of automated affect recognition. With growing citation impact, Chatterjee’s research is shaping next-generation systems that interpret human emotion through thermal signatures, offering a more resilient alternative to conventional visual methods. His innovative approach continues to inspire new directions in both computer vision and affective computing.