Security Monitoring System Using FaceNet For Wireless Sensor Network

Abstract

Face Recognition techniques have been rising rapidly over past few decades and gaining attraction in many security systems. Several methodologies are proposed to provide excellent results in face detection. Sensing technology enables several applications such as transportation, healthcare and security. Video surveillance systems trace and identify moving objects. Wireless Sensor networks are used to monitor remote areas and can be applied to monitor a facility by considering each camera as sensor nodes. Cameras are used as nodes in a wireless sensor network with a central server or a gateway node for all the monitoring and analysis of the information retrieved from the nodes. Identification and authentication of users in any organization is quite difficult due to high movement. Face recognition can be used detect faces and identify them continuously in a video feed which can be deployed to continuously monitor an area. Feeding from camera to base station uses Multi-task Cascaded Convolutional Neural Networks (MCTNN) and FaceNet algorithms for face recognition. Further information about the person is sent to all the end-user nodes present in the wireless network. This approach has been implemented and evaluated on a prototype wired camera network called FaceNet to monitor a network and provide security. A method for tracking people in 2D world coordinates and acquiring canonical frontal face images that fits the sensor network paradigm. The approach evaluates and demonstrates the tasking algorithm in action on data acquired from the FaceNet camera network.