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@article{146398,
        author = {Deepak Kumar and Akash  Shejwal and Jayshree Kolte and Sayli Choudhari and Raghunath  Kawle},
        title = {Automated Attendance System Using HOG Feature},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {12},
        pages = {440-442},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146398},
        abstract = {Automated face recognition technologies have seen dramatic improvement in performance over the past years and such systems are widely used for security and commercial applications. As students are increasing day by day it is difficult task for colleges or universities to maintain the records of students. Conventional methods of taking attendance is time consuming and required more efforts, therefore in this paper we used face recognition technology for marking attendance of students automatically. There are some automated systems available which involve biometrics like fingerprint and iris which are well developed in recent years but are intrusive and also cost required for development on large scale is more, to overcome these issues face recognition is used. HOG feature is used for acquire desired result. This paper proposes a design to detect faces real time using HOG descriptor. The problems like proxy attendance and time of manual attendance system is solved by this system.
},
        keywords = {Histogram of Oriented Gradients (HOG), HOG descriptor, Face recognition,Haar cascade.
},
        month = {},
        }