Live video face recognition using raspberry pi
Abstract
Face Detection and Recognition is a challenging area of computer vision that involves in identification of human faces. Face recognition has a lot of applications in real-time like in security, accessibility, and even in payments. Since the number of applications increases, there is a need of more efficient, reliable and low-cost face recognition system in today’s world. The aim of the paper is to develop such type of face recognition system using Raspberry Pi device. The setup consists of a Raspberry Pi 4 Model B device with a camera module attached. The camera is used to take the input images of any person and store them to train our model. The proposed model makes use of OpenCV, TheHaar Cascadeclassifiers for face detection and the HOG(Histogram of Gradient Descent) + SVM classifiers for real time face recognition. After vigorous testing the overall complexity and accuracy of the model the system is proved to be efficient and robust.
References
[2] W.-Y. Zhao, R. Chellappa, P. J. Phillips, and A. Rosenfeld, “Face recognition: A literature survey,” ACM Comput. Surv., vol. 35, pp. 399–458, 12 2003.
[3] D. King, “Dlib-ml: A machine learning toolkit,” Journal of Machine Learning Research, vol. 10, pp. 1755–1758, 07 2009.
[4] K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, “Joint face detection and alignment using multitask cascaded convolutional networks,” IEEE Signal Processing Letters, vol. 23, 04 2016.
[5] R. Hasan and A. Sallow, “Face detection and recognition using opencv,” Journal of Soft Computing and Data Mining, vol. 2, 10 2021.
[6] R. Padilla, C. Filho, and M. Costa, “Evaluation of haar cascade classifiers for face detection,” 04 2012.
[7] F. Ahmad, A. Najam, and Z. Ahmed, “Image-based face detection and recognition: ”state of the art”,” IJCSI International Journal of Computer Science Issues, vol. 9, 02 2013.
[8] Zhi, Hui, and Sanyang Liu. ”Face recognition based on genetic algorithm.” Journal of Visual Communication and Image Representation 58 (2019): 495-502.
[9] Moussa, Mourad, MahaHmila, and Ali Douik. ”A novel face recognition approach based on genetic algorithm optimization.” Stud. Inform. Control 27.1 (2018): 127-134. A. Benton, “Facial recognition 1990,” Cortex, vol. 26, no. 4, pp. 491–499, 1990.
[10] P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” vol. 1, pp. I–511, 02 2001.
[11] Gondole, Devendra, and P. A. Salunkhe. ”Face Recognition Based On Local Binary Pattern.” (2018).
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