Face recognition from a partial face view by partitioning and rotating facial images
Keywords:
Face detection, Face recognition, Viola-Jones algorithm, Eigen-faces, Face SplittingAbstract
This paper presents a novel technique for Face Recognition from a Partial Face View (FRPV), which consists of three phases. The first phase uses an existing algorithm to detect faces in input images. The second phase includes splitting the input images undetected by the first phase into two, four, six, or eight parts. Then, every part is rotated by a new split and rotate face detection (SRFD) algorithm until it detects a face in one of these partial images. The third phase uses the Eigenfaces method with train and test databases to perform recognition. This phase compares the selected test image with images in the train database until it recognizes the person and updates the train database. The FRPV system was implemented using a head-pose image database where every person has multiple images with several poses having different Pitch and Yaw Angles ranging from –90º to +90º. The results showed that the FRPV system outperformed previous methods. Its accuracy rate was equal to 96% for faces that had different poses. In addition, the SRFD method achieved a detection success rate of 67%, which is better than other similar methods.
References
Ibrahim, D.R., Tamimi A.A. and Abdalla, A.M.2017.“Performance analysis of biometric recognition modalities,” In the 8th International
Conference on Information Technology, Amman, Jordan. DOI: 10.1109/ICITECH.2017.8079977
Farfade, S.S. and Saberian, M., Li, L.-J.2015.“Multi-View Face Detection Using Deep Convolutional Neural Networks,”Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, pp.643-650.DOI: 10.1145/2671188.2749408
Naik,R. and Lad, K.2016.“A Review on Side-View Face Recognition Methods,”International Journal of Innovative Research in Computer and Communication Engineering, vol.4, no.3, pp.2943-2991. DOI: 10.15680/IJIRCCE.2016.0403015
Hirayama,K. and Saiki, S., Nakamura, M. 2019. “Developing RealTime Face Identification Device Composable with Distributed Applications,” In: Duffy, V. (ed) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Body and Motion. HCII 2019. Lecture Notes in Computer Science, vol.11581, pp.420-432.DOI: 10.1007/978-3-030-22216-1_31
Kato, H., Chakraborty, G. and Chakraborty, B.2012. “A Real-Time Angle- and Illumination-Aware Face Recognition System Based on
Artificial Neural Network,”Applied Computational Intelligence and Soft Computing, vol.2012, Article ID 274617, 9 pages.DOI: 10.1155/2012/274617
Al-Allaf, O.N., Tamimi, A.A. and Alia, M.A.2013. “Face recognition system based on different artificial neural networks models and training algorithms,”International Journal of Advanced Computer Science and Applications, vol.4, no.6, pp.40-47. DOI:10.14569/ijacsa.2013.040606
Alia, M.A., Tamimi, A.A. and Al-Allaf, O.N.A. Dec. 2013. “Integrated System for Monitoring and Recognizing Students During Class Session,”International Journal of Multimedia & Its Applications, vol.5, no.6, pp.45-52.DOI : 10.5121/ijma.2013.5604
Tamimi, A.A., AL-Allaf, O.N.A. and Alia, M.A.2015. “Real-Time Group Face-Detection for an Intelligent Class-Attendance System,”International Journal of Information Technology and Computer Science, vol.6, pp.66-73.DOI: 10.5815/ijitcs.2015.06.09
Ranjan, R., Bansal, A., Zheng, J., Xu, H., Gleason, J., Lu, B., Nanduri, A., Chen, J.-C., Castillo, C.D. and Chellappa, R.April 2019. “A Fast and Accurate System for Face Detection, Identification and Verification,” In IEEE Transactions on Biometrics, Behavior, and Identity Science, vol.1, no.2, pp.82-96.DOI: 10.1109/TBIOM.2019.2908436
Masayuki Tanaka (2019). Face Parts Detection (https://www.mathworks.com/matlabcentral/fileexchange/36855-face-parts-detection), MATLAB Central File Exchange. Retrieved October 12, 2019.
Naik, R.K. and Lad, K.B. 2017. “Human Recognition from Multi Angled Images,”International Conference on Research and Innovations in Science, Engineering &Technology, ICRISET2017 (Kalpa Publications in Computing), vol.2, pp.1–12. https://easychair.org/publications/open/JtJQ
Pearline, S.A. and Hemalatha, M.2016. “Face Recognition Under Varying Blur, Illumination and Expression in an Unconstrained Environment,”CIC 2016 Special Issue International Journal of Computer Science and Information Security, vol.14, pp.48-54. https://arxiv.org/ftp/arxiv/papers/1902/1902.10885.pdf
Pang, M., CheungY., Wang, B. and Liu, R.2019. “Robust heterogeneous discriminative analysis for face recognition with single sample per person,”Pattern Recognition, vol.89, pp.91-107.DOI: 10.1016/j.patcog.2019.01.005
Rajamanoharan, G. andCootes, T.F.Dec. 2015. “Multi-View Constrained Local Models for Large Head Angle Facial Tracking,”2015 IEEE International Conference on Computer Vision Workshop (ICCVW), Santiago, pp.971-978.DOI: 10.1109/ICCVW.2015.128
Viola, P. and Jones, J.2001. “Robust Real-time Object Detection,”Technical Report CRL 2001/01, Cambridge Research Laboratory. https://www.hpl.hp.com/techreports/CompaqDEC/CRL-2001-1.pdf
Barnouti, N.H., Al-Dabbagh, Muhammed, S.S.M. and Al-Bamarni, H.J.Sept. 2016.“Real-Time Face Detection and Recognition Using
Principal Component Analysis (PCA) – Back Propagation Neural Network (BPNN) and Radial Basis Function (RBF),”Journal of Theoretical and Applied Information Technology, vol.91, no.1. ISSN: 1817-3195.
Troitsky, A.2016.“Two-Level Multiple Face Detection Algorithm Based on Local Feature Search and Structure Recognition Methods,”International Journal of Applied Eng. Research, vol.11, no.6, pp.4640-4647.
Yang, S., Luo, P., Loy, C.C. and Tang, X. 2016.“Wider Face: A Face Detection Benchmark,”2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, pp.5525-5533.DOI: 10.1109/CVPR.2016.596
Islam, M., Naeem, A. and Hasan, N.May 2017.“Comparison between Viola-Jones and KLT Algorithms and Error Correction of Viola-Jones Algorithm,”International Journal of Computer Engineering and Applications, vol.11, no.5. ISSN 2321-3469.
Orozco, J., Martinez, B. and Pantic, M. 2015.“Empirical analysis of cascade deformable models for multi-view face detection,”Image
and Vision Computing, vol.42, pp.47-61.DOI: 10.1016/j.imavis.2015.07.002
Shehzad, M.I., Awais, M., Amin, M. and Shah, Y.A.2014.“Face Recognition Using Average Half Face Template,”International Journal of Technology, vol.2, pp.159-168.DOI: 10.14716/ijtech.v5i2.408
Gourier, N., Hall, D. and Crowley, J.L.2004.“Estimating Face Orientation from Robust Detection of Salient Facial Features,”Proceedings of Pointing 2004, ICPR, International Workshop on Visual Observation of Deictic Gestures, Cambridge, UK.
Tamimi, A., AL-Allaf, O.N.A. and Alia, A.Feb. 2015.“Eigen Faces and Principle Component Analysis for Face Recognition Systems: A
Comparative Study,”International Journal of Computers & Technology, vol.14, no.4, pp.5650-5660. DOI:10.24297/ijct.v14i4.1967
Khryashchev, V.V., Lebedev, A.A. and Priorov, A.L. 2017. “Enhancement of Fast Face Detection Algorithm Based on A Cascade of Decision Trees,”The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol.42, no.2/W4, pp.237-241. DOI: 10.5194/isprs-archives-XLII-2- W4-237-2017
Soni, L.N., Datar, A. andDatar, S. Sept./Oct. 2017. “Implementation of Viola-Jones Algorithm Based Approach for Human Face Detection,”International Journal of Current Engineering and Technology, vol.7, no.5, pp.1819-1823. E-ISSN 2277 – 4106.
Scherhag, U., Rathgeb, C., Merkle, J., Breithaupt, R. and Busch, C.2019. “Face Recognition Systems Under Morphing Attacks: A Survey,” IEEE Access, vol.7, pp.23012-23026.DOI: 10.1109/access.2019.2899367
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2019 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
