In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and health care. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking and graph model-based tracking. Closed-circuit television (CCTV) surveillance systems have made tremendous technological progress in the last decade, not only in individual capabilities, but also in the ability to interface with other security technology.Originally, CCTV surveillance systems were simply a deterrent. The notion that “Big Brother” was watching was often enough to keep people from misbehaving. Today, though, CCTV surveillance systems are common enough that they have lost their novelty, reducing effectiveness as a simple deterrent, especially for illegal entry or violent crime.
So we thought of making an AI based Activity Tracking and Parking Assistance based system which can easily be implemented in parking lots and garages in malls , housing complexes etc. Our entire system is based on Open-Sourced software and hardware. We are using a complex but user compatibiltiy system of mixing technology with the social cause.A fully functional and deployable prototype of our product would consist of a highly powerful NVIDIA Jetson Nano 4GB Developer Board costing $99 each alongwith Logitech C270 Webcams costing $40 each (even cheaper ones can be deployable). The amount of the hardware is completely case sensitive as it resides with the amount of area of the parking lot/garage. On an average the total cost of the setup would be around $300 whereas the previous setup would cost around $800. So the system is both feasable and reliable.