Virtual Trailroom

EasyChair Preprint no. 10109

Abstract

The virtual trail room system receives a real-time video feed from a camera and processes data with the OpenCV computer vision library and Haarcascade classifier. In order to correctly identify faces in the video feed, the Haarcascade classifier is trained on a sizable dataset of human faces. OpenCV’s computer vision algorithms then extract attributes from the discovered faces and follow the faces’ movements in real-time.The Dlib, which offers a secure and scalable method for storing and retrieving massive volumes of data, is used to store the information gathered in a database. This makes it possible for the system’s data to be managed and analysed effectively. The virtual trail room system can be set up to provide notifications in the event of unexpected movement patterns or behaviour, enabling proactive intervention and enhancing security. This makes it perfect for usage in a range of environments, including office buildings, public areas, and retail outlets, where real-time tracking and monitoring of people is necessary to maintain safety and security.The virtual trail room system’s affordability is one of its main advantages. The virtual trail room system may function independently, which eliminates the need for additional employees and associated expenditures, in contrast to typical security systems that demand the presence of physical security officers. The system is also quite effective at tracking and monitoring people in real time, which is crucial for maintaining the safety and security of the building.The virtual trail room system can reliably detect and track human faces even in difficult lighting circumstances because to the usage of cutting-edge computer vision techniques like the Haarcascade classifier and OpenCV. Also, the system is quite expandable, enabling the integration of extra cameras and sensors as needed.

Keyphrases: computer vision, Dlib, Haarcascade classifier, Real-time tracking, Virtual trail room system

@Booklet{EasyChair:10109,
  author = {Peter Soosai Anandaraj and Purna Venakata Sri Sai Kandagatla and Naga Praveen J Kumar and Narasimha Sai Chilmakuri},
  title = {Virtual Trailroom},
  howpublished = {EasyChair Preprint no. 10109},

  year = {EasyChair, 2023}}