Facial Micro Expression Recognition for Feature Point Tracking using Apex Frames on CASME II Database
DOI:
10.33395/sinkron.v8i1.11946Keywords:
apex frame, KLT, micro-expressions, motion features, point feature trackingAbstract
Micro-expressions are facial expressions that occur inadvertently to hide true feelings (emotional leaks). Although previous studies used the entire face area and all frames in the video dataset, this resulted in relatively long computation time and data redundancy. The main contribution of this research is to apply recognition micro-expression analysis using a comparison of apex frames with manual (handcrafted) and random sampling of frames and applying feature point tracking to the brow area and corners of the lips. The method for forming feature points in the facial area uses Discriminative Response Map Fitting (DRMF), then facial feature points are tracked using Kanade-Lucas-Tomasi (KLT). This feature point tracking produces motion feature data as feature extraction data. Finally, a comparative analysis of the classification method using the Support Vector Machine (SVM) and MLP-Backpropagation was conducted using the CASME II dataset. The experimental results of this study show significant results with an accuracy of 81.3% on MLP-Backpropagation and an average computing time of 1.45 seconds for each video. From the results of this study, information on the apex phase can contribute information that is very important for facial micro-expression recognition.
Downloads
References
Asmara, R. A., P. Choirina, C. Rahmad, A. Setiawan, F. Rahutomo, R. D. R. Yusron, and U. D. Rosiani. 2019. “Study of DRMF and ASM Facial Landmark Point for Micro Expression Recognition Using KLT Tracking Point Feature.” Journal of Physics: Conference Series 1402:077039–077039. doi: 10.1088/1742-6596/1402/7/077039.
Asthana, Akshay, Stefanos Zafeiriou, Shiyang Cheng, and Maja Pantic. 2013. “Robust Discriminative Response Map Fitting with Constrained Local Models.” Pp. 3444–51 in Proceedings of the IEEE conference on computer vision and pattern recognition.
Ben, Xianye, Yi Ren, Junping Zhang, Su-Jing Wang, Kidiyo Kpalma, Weixiao Meng, and Yong-Jin Liu. 2021. “Video-Based Facial Micro-Expression Analysis: A Survey of Datasets, Features and Algorithms.” IEEE Transactions on Pattern Analysis and Machine Intelligence 1–1. doi: 10.1109/TPAMI.2021.3067464.
Choirina, Priska, and Ulla Delfana Rosiani. 2020. “Detection and Tracking of Face Location in the Pre-processing Stage of Recognition of Micro Expressions Using the Kanade-Lucas-Tomasi (KLT) Method.” Jurnal Informatika Polinema 7(1):73–78. doi: 10.33795/jip.v7i1.467.
Ekman, Paul. 2009. “Lie Catching and Microexpressions.” The Philosophy of Deception 1(2):5.
Ekman, Paul, and Wallace V. Friesen. 1971. “Constants across Cultures in the Face and Emotion.” Journal of Personality and Social Psychology 17(2):124–29. doi: 10.1037/h0030377.
Hashmi, Mohammad Farukh, B. Kiran Kumar Ashish, Vivek Sharma, Avinash G. Keskar, Neeraj Dhanraj Bokde, Jin Hee Yoon, and Zong Woo Geem. 2021. “LARNet: Real-Time Detection of Facial Micro Expression Using Lossless Attention Residual Network.” Sensors 21(4):1098. doi: 10.3390/s21041098.
He, Jun, Li Peng, Bo Sun, Lejun Yu, and Meng Guo. 2021. “Dual Multi-Task Network with Bridge-Temporal-Attention for Student Emotion Recognition via Classroom Video.” Pp. 1–8 in 2021 International Joint Conference on Neural Networks (IJCNN).
Jianbo Shi and Tomasi. 1994. “Good Features to Track.” Pp. 593–600 in 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
Jordan, Sarah, Laure Brimbal, D. Brian Wallace, Saul M. Kassin, Maria Hartwig, and Chris NH Street. 2019. “A Test of the Micro-Expressions Training Tool: Does It Improve Lie Detection?” Journal of Investigative Psychology and Offender Profiling 16(3):222–35.
Liong, Sze-Teng, Y. S. Gan, Wei-Chuen Yau, Yen-Chang Huang, and Tan Lit Ken. 2018. “OFF-ApexNet on Micro-Expression Recognition System.” ArXiv:1805.08699 [Cs].
Liong, Sze-Teng, John See, KokSheik Wong, and Raphael C. W. Phan. 2018. “Less Is More: Micro-Expression Recognition from Video Using Apex Frame.” Signal Processing: Image Communication 62:82–92. doi: 10.1016/j.image.2017.11.006.
Lu, Hua, Kidiyo Kpalma, and Joseph Ronsin. 2018. “Motion Descriptors for Micro-Expression Recognition.” Signal Processing: Image Communication 67:108–17. doi: 10.1016/j.image.2018.05.014.
O’Sullivan, Maureen, Mark G. Frank, Carolyn M. Hurley, and Jaspreet Tiwana. 2009. “Police Lie Detection Accuracy: The Effect of Lie Scenario.” Law and Human Behavior 33(6):530.
Ringeval, Fabien, Michel Valstar, Erik Marchi, Denis Lalanne, and Roddy Cowie. 2015. “The AV+ EC 2015 Multimodal Affect Recognition Challenge: Bridging across Audio, Video, and Physiological Data Categories and Subject Descriptors.” in Proc. ACM Multimedia Workshops.
Rosiani, Ulla Delfana, Ariadi Retno Tri Hayati Ririd, Priska Choirina, Adri Gabriel Sooai, Surya Sumpeno, and Mauridhi Hery Purnomo. 2018. “Micro Expression: Comparison of Speed and Marking Accuracy in Facial Component Detection.” Pp. 221–26 in 2018 International Conference on Computer Engineering, Network and Intelligent Multimedia (CENIM).
Tran, Thuong-Khanh, Quang-Nhat Vo, Xiaopeng Hong, Xiaobai Li, and Guoying Zhao. 2020. “Micro-Expression Spotting: A New Benchmark.” ArXiv:2007.12421 [Cs].
Yan, Wen-Jing, Su-Jing Wang, Yu-Hsin Chen, Guoying Zhao, and Xiaolan Fu. 2014. “Quantifying Micro-Expressions with Constraint Local Model and Local Binary Pattern.” Pp. 296–305 in European Conference on Computer Vision. Springer.
Yao, Yongqiang, Di Huang, Xudong Yang, Yunhong Wang, and Liming Chen. 2018. “Texture and Geometry Scattering Representation-Based Facial Expression Recognition in 2D+3D Videos.” ACM Transactions on Multimedia Computing, Communications, and Applications 14(1s):18:1-18:23. doi: 10.1145/3131345.
Yongyong, Duan, He Xinhua, Wu Zongling, and others. 2020. “Image Stabilization Algorithm Based on KLT Motion Tracking.” Pp. 44–47 in 2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL). IEEE.
Zhang, Shiyu, Bailan Feng, Zhineng Chen, and Xiangsheng Huang. 2017. “Micro-Expression Recognition by Aggregating Local Spatio-Temporal Patterns.” Pp. 638–48 in MultiMedia Modeling, Lecture Notes in Computer Science, edited by L. Amsaleg, G. Þ. Guðmundsson, C. Gurrin, B. Þ. Jónsson, and S. Satoh. Cham: Springer International Publishing.
Zhu, Xuena, Xianye Ben, Shigang Liu, Rui Yan, and Weixiao Meng. 2018. “Coupled Source Domain Targetized with Updating Tag Vectors for Micro-Expression Recognition.” Multimedia Tools and Applications 77(3):3105–24. doi: 10.1007/s11042-017-4943-z.
Downloads
|
How to Cite
Issue
Section
License
Copyright (c) 2023 Priska Choirina, Ulla Delfana Rosiani , Indah Martha Fitriani; Rijalul Baqi
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Muhammad Khoiruddin harahap
Google Scholar 
Moraref
PKP Index
Garuda Kemdikbud
Indonesia OneSearch
OCLC Worldcat
Dimensions
Index Copernicus
Scilit
