Stereo Vision Based Robot for Remote Monitoring with VR Support
This addresses remote monitoring for users needing immersive surveillance, but it is incremental as it combines existing technologies like stereo vision, robotics, and machine learning.
The paper tackles remote monitoring by developing a stereo vision-based 3-DOF robot that streams real-time 3D stereoscopic video to users via VR, enabling first-person experiences and object tracking using deep neural networks, with a full working prototype demonstrated.
The machine vision systems have been playing a significant role in visual monitoring systems. With the help of stereovision and machine learning, it will be able to mimic human-like visual system and behaviour towards the environment. In this paper, we present a stereo vision based 3-DOF robot which will be used to monitor places from remote using cloud server and internet devices. The 3-DOF robot will transmit human-like head movements, i.e., yaw, pitch, roll and produce 3D stereoscopic video and stream it in Real-time. This video stream is sent to the user through any generic internet devices with VR box support, i.e., smartphones giving the user a First-person real-time 3D experience and transfers the head motion of the user to the robot also in Real-time. The robot will also be able to track moving objects and faces as a target using deep neural networks which enables it to be a standalone monitoring robot. The user will be able to choose specific subjects to monitor in a space. The stereovision enables us to track the depth information of different objects detected and will be used to track human interest objects with its distances and sent to the cloud. A full working prototype is developed which showcases the capabilities of a monitoring system based on stereo vision, robotics, and machine learning.