Abstract
Nowadays, facial recognition technology (FRT) has come into focus because of its various applications in security and non-security perspective. It provides a secure solution for identification and verification of person identity. Accurate localization of facial features plays a significant role for many facial analysis applications including biometrics and emotion recognition. There are several factors that make facial feature localization a challenging problem. Facial expression is one of the influential factors of FRT. The paper proposes a new geometric-based hybrid technique for automatic localization of facial features in frontal and near-frontal neutral and expressive face images. A graphical user interface (GUI) is designed that could automatically localize 16 landmark points around eyes, nose, and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Bosphorous database. Also, the system is tested on DeitY-TU face database. The performance of the proposed method has been done in terms of error measures and accuracy. The detection rate of the proposed method is 96.03 % on JAFFE database, 94.06 % on DeitY-TU database, and 94.21 % on Bosphorous database.
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Acknowledgments
The work presented here was conducted in the Biometrics Laboratory of Department of Computer Science and Engineering of Tripura University (A central university), Tripura, Suryamaninagar-799,022. The research work was supported by the Grant No. 12(2)/2011-ESD, Dated 29/03/2011 from the DeitY, MCIT, Government of India.
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Roy, S.D., Saha, P., Bhowmik, M.K., Debnath, D. (2016). Performance Evaluation of Geometric-Based Hybrid Approach for Facial Feature Localization. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_22
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DOI: https://doi.org/10.1007/978-981-10-0448-3_22
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