Abstract
Usage of the system for human emotion recognition has been increased in various types of applications of affective computing fields such as human sign language understanding, identification of human mental disorder, and human-computer interaction. Here, we report a video frame-based procedure for the estimation of human emotional behavior. We introduce Circumradius-Incenter-Circumcenter combined geometric signature (CIC) induced from our proposed triangulation method. The method first includes the step of salient landmark identification from face image frames by using the Active Appearance Model (AAM). Here, we fetch geometric features from triangles drawn by landmark points, thereafter core triangles are found based on the CIC feature which plays an important role to get an interpretation of changing information of human emotions. In the end, the extracted core features from core triangles are employed into the Multilayer Perceptron (MLP) classifier to get recognition accuracy. The discrimination power of our proposed system is evaluated on well-known three benchmark video face frame databases, viz., CK+, MMI, and MUG. Moreover, the performance of the proposed procedure is validated by presenting the comparison task with other existing methods.
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Acknowledgements
The authors want to state their gratefulness to Prof. Maja Pantic and Dr. A. Delopoulos for making available to use the MMI and MUG databases. The authors also like to express thanks to Department of Science and Technology, Ministry of Science and Technology, Government of India, for supporting with DST-INSPIRE Fellowship (INSPIRE Reg. no. IF160285, Ref. No.: DST/INSPIRE Fellowship/[IF160285]) to carry out research work. The authors are thankful to Department of Computer & System Sciences, Visva-Bharati University for providing infrastructure support.
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Nasir, M., Dutta, P., Nandi, A. (2021). Recognition of Transforming Behavior of Human Emotions from Face Video Sequence: A Triangulation-Induced Circumradius-Incenter-Circumcenter Combined Approach. In: Bhattacharyya, S., Dutta, P., Datta, K. (eds) Intelligence Enabled Research. Advances in Intelligent Systems and Computing, vol 1279. Springer, Singapore. https://doi.org/10.1007/978-981-15-9290-4_9
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