The revolutionary way to fully understand vehicle behaviour

Connection of multiple fields of view to reconstructing the complete trajectory of people and vehicles

The Multi-Camera Tracking Module drastically increases the potential of Sprinx deep learning-based video analytics for vehicle and people mobility, such as and co.exist, in tunnels and intersections.

The activation of this Module enables the connection of multiple fields of view to reconstruct the complete trajectory of people and vehicles and make mobility even safer, smarter, more sustainable, and efficient.


Acting like a 'SUPERCAMERA'

The objects that move in the field of view of different cameras are correlated through their trajectories. The Multi-Camera Tracking Module allows reconstructing their path within the survey area. In this way, the single behaviour of a pedestrian or a vehicle, which within a single shot could be expected, with a global and comprehensive vision could bring out an anomaly of movement, thus generating action scenarios for control room operators.
The Multi-Camera Tracking Module completely revolutionizes the perspective with which vehicle behaviour is analyzed and attributes greater effectiveness and efficiency to traffic monitoring systems.

Key Features
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Supercamera View
Complete tracking of people and vehicles within a wide
area impossible to be covered by a single camera
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The Module allows the AI-based Sprinx video analysis
systems to generate a global model of the system (road, tunnel, roundabout,
intersection), reconstructing the general perspective.
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Detecting anomalous behaviours within the road section, such as sudden decelerations or distraction while driving, increasing the degree of safety and efficiency in traffic monitoring
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In case of tampering or the simple maintenance of the CCTV system, the Sprinx AI-based video analysis platform recalibrates itself
In the event of an accident inside a tunnel, geolocation of it and indication of the actual number of vehicles, by class, present inside the tunnel
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AI based
The combination of 3D object tracking and Deep-Learning mosule, drastically increases the degree of efficiency and effectiveness of mobility analysis systems, inside tunnels and outdoor
Application Field