Abstract
Facial recognition system is used widely to identify and verify the person’s face from image or video source. With the continuous expansion of the surveillance system, surveillance cameras not only bring convenience, but also produce a massive amount of monitoring data, which poses huge challenges to storage, analytics, and retrieval. The smart monitoring system equipped with intelligent video analytics technology can monitor as well as pre-alarm abnormal events or behaviors. Here, propose system will detect the intruder and inform the security within seconds. The Nvidia Jetson Nano board will be used to compute convolutional neural network algorithm for the facial recognition process. The basic idea will be to use this system where a database can be stored of the existing faces. The system will then take the data from the surveillance camera and run facial recognition algorithm on it. It will match all the faces with the ones already stored in the database and if it finds any face which is new, it will send an alert to the security personnel. This will help to increase the security of the place where there are many people gathered at a time, for example, schools, colleges, universities, etc.
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Shaikh, M.U., Vora, D., Anurag, A. (2021). Surveillance System for Intruder Detection Using Facial Recognition. In: Balas, V.E., Semwal, V.B., Khandare, A., Patil, M. (eds) Intelligent Computing and Networking. Lecture Notes in Networks and Systems, vol 146. Springer, Singapore. https://doi.org/10.1007/978-981-15-7421-4_18
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DOI: https://doi.org/10.1007/978-981-15-7421-4_18
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