References
- A. Mehrabian, “Communication without words,” Psychol. Today, Vol. 2, no. 4, pp. 53–55, Sep. 1968.
- E. Sariyanidi, H. Gunes, and A. Cavallaro, “Automatic analysis of facial affect: A survey of registration, representation and recognition,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 37, no. 6, pp. 1113–1133, Jun. 2015.
- X. Zhao and S. Zhang, “A review on facial expression recognition: Feature extraction and classification,” IETE Tech. Rev., Vol. 33, no. 5, pp. 505–517, Jan. 2016.
- S. Zhang, X. Zhao, Y. Chuang, W. Guo, and Y. Chen, “Learning discriminative dictionary for facial expression recognition,” IETE Tech. Rev., Vol. 35, no. 3, pp. 275–281, Feb. 2017.
- P. Carcagnì, M. Del Coco, M. Leo, and C. Distante, “Facial expression recognition and histograms of oriented gradients: A comprehensive study,” SpringerPlus, Vol. 4, no. 1, pp. 645, Dec. 2015.
- U. Mlakar and B. Potočnik, “Automated facial expression recognition based on histograms of oriented gradient feature vector differences,” Signal Image Video Process., Vol. 9, no. 1, pp. 245–253, Dec. 2015.
- D. Shuman, S. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, “The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains,” IEEE Signal Process. Mag., Vol. 30, no. 3, pp. 83–98, May 2013.
- X. He and P. Niyogi, “Locality preserving projections,” in Proceedings of Advances in Neural Information Processing Systems, Cambridge, MA: MIT Press, 2003, pp. 153–160.
- X. He, S. Yan, Y. Hu, P. Niyogi, and H. Zhang, “Face recognition using Laplacian faces,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 27, no. 3, pp. 328–340, Mar. 2005.
- H. K. Meena, K. K. Sharma, and S. D. Joshi, “Improved facial expression recognition using graph signal processing,” Electron. Lett., Vol. 53, no. 11, pp. 718–720, May 2017.
- H. K. Meena, K. K. Sharma, and S. D. Joshi, “Facial expression recognition with enhanced feature extraction using graph Fourier transform,” in IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), IEEE, Sep. 2017, pp. 2887–2891.
- H. K. Meena, K. K. Sharma, and S. D. Joshi, “Feature fusion of HOG and GSP for smile recognition,” in International Conference on Augmented Reality, Virtual Reality and Computer Graphics, Springer, Jun. 2017, pp. 402–409.
- N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, USA, Vol. 1, Jun. 2005, pp. 886–893.
- P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” Proceedings of IEEE Computer Vision and Pattern Recognition (CVPR), Kauai, USA, Vol. 1, 2001, pp. I–511.
- M. Lyons, S. Akamatsu, M. Kamachi, and J. Gyoba, “Coding facial expressions with Gabor wavelets,” in Proceedings of IEEE International Conference on Face and Gesture Recognition, Nara, Japan, Apr. 1998, pp. 200–205.
- P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews, “The extended Cohn–Kanade dataset (CK+): A complete dataset for action unit and emotion-specified expression,” in Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), San Francisco, USA, IEEE, Jun. 2010, pp. 94–101.
- L. Zhang and D. Tjondronegoro, “Facial expression recognition using facial movement features,” IEEE Trans. Affective Comput., Vol. 2, no. 4, pp. 219–229, Oct. 2011.
- A. Poursaberi, H. A. Noubari, M. Gavrilova, and S. N. Yanushkevich, “Gauss–Laguerre wavelet textural feature fusion with geometrical information for facial expression identification,” EURASIP J. Image Video Process., Vol. 2012, no. 1, pp. 1–13, Dec. 2012.
- L. Zhong, Q. Liu, P. Yang, B. Liu, J. Huang, and D. N. Metaxas, “Learning active facial patches for expression analysis,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Rhode Island, USA, IEEE, Jun. 2012, pp. 2562–2569.
- S. L. Happy and A. Routray, “Automatic facial expression recognition using features of salient facial patches,” IEEE Trans. Affective Comput., Vol. 6, no. 1, pp. 1–12, Jan. 2015.
- C. Shan, S. Gong, and P. W. McOwan, “Facial expression recognition based on local binary patterns: A comprehensive study,” Image Vis Comput, Vol. 27, no. 6, pp. 803–816, May 2009.
- S. L. Happy and A. Routray, “Robust facial expression classification using shape and appearance features,” in Proceedings of International Conference on Advances in Pattern Recognition (ICAPR), Kolkata, India, IEEE, Jan. 2015, pp. 1–5.
- J. Chen, Z. Cheni, Z. Chi, and H. Fu, “Facial expression recognition based on facial components detection and hog features,” in Proceedings of International Workshops on Electrical and Computer Engineering Subfields, Turkey, Aug. 2014, pp. 884–888.