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Review Paper | Computer Science | Volume 15 Issue 6, June 2026 | Pages: 1341 - 1349 | India
A Comprehensive Survey of Facial Expression Recognition Methods for Basic and Compound Emotions Under Occluded and Non-Occluded Conditions
Abstract: Facial Expression Recognition (FER) is a technology that enables the automatic identification and interpretation of human emotions from facial images or videos. FER plays a major role in various fields such as neuro science, bio medical engineering, health care, education human computer interaction and public safety. Most of the existing methods provides solution to the problem of facial expression recognition either by considering the local patches of face or by using the global image. The field of FER faces many challenges such as pose variation, low resolution images, aging effects, variation in lighting, intra class variations, inter class similarities and partial occlusion. Among these, partial occlusion is very challenging since it hides important facial information leading to poor emotion recognition accuracy of the system. This survey provides a detailed analysis of various FER methods and focusing on occlusion and non-occluded conditions. The proposed study analyses different methods for recognizing facial expressions. Also, it portrays the current trends in technologies, datasets and various tools used for FER.
Keywords: facial expression recognition (fer), basic expression, compound expression, micro expression, convolutional neural network (cnn)
How to Cite?: Aparna V B, Ajitha R S, "A Comprehensive Survey of Facial Expression Recognition Methods for Basic and Compound Emotions Under Occluded and Non-Occluded Conditions", Volume 15 Issue 6, June 2026, International Journal of Science and Research (IJSR), Pages: 1341-1349, https://www.ijsr.net/getabstract.php?paperid=SR26622120142, DOI: https://dx.doi.org/10.21275/SR26622120142