Methods and systems for detecting intrusions in a monitored volume

A method for determining a tridimensional location of a camera for a self-calibrated monitoring system, in which a plurality of N tridimensional sensors respectively monitor at least a part of the monitored volume and respectively communicate with a central processing unit,

• providing a camera comprising at least one reflective pattern such that a data point of said reflective pattern acquired by a tridimensional sensor of the self-calibrated monitoring system can be associated to said camera,
• in the monitored volume, in a field of view of at least one sensor of the plurality of N tridimensional sensors so that said sensor acquire a local point cloud comprising at least one tridimensional data point of the reflective pattern of the camera,
• receiving a local point cloud from said at least one tridimensional sensor and computing an aligned local point cloud by aligning said local point cloud with the global tridimensional map of the self-calibrated monitoring system,
• identifying, in the aligned local point cloud at least one data point corresponding to the reflective pattern of the camera, and
• determining at least a tridimensional location of the camera in a global coordinate system of the global tridimensional map on the basis of the coordinates of said identified data point of the aligned local point cloud corresponding to the reflective pattern of the camera.

A self-calibrated monitoring system for detecting intrusions in a monitored volume, the system comprising:

• a plurality of N tridimensional sensors respectively able to monitor at least a part of the monitored volume, each sensor of said plurality of N tridimensional sensors being able to acquire a local point cloud in a local coordinate system of said sensor, said local point cloud comprising a set of tridimensional data points of object surfaces in a local volume surrounding said sensor and overlapping the monitored volume
• a memory to store said local point cloud and a global tridimensional map of a monitored volume comprising a set of tridimensional data points of object surfaces in a monitored volume, the local volume at least partially overlapping the monitored volume,
• a central processing unit able to receive the acquired local point clouds from the plurality of N tridimensional sensors, store said acquired point clouds in a memory and,
• for each sensor of said plurality of N tridimensional sensors,
• compute updated tridimensional position and orientation of said sensor in a global coordinate system of the monitored volume by aligning a local point cloud acquired by said tridimensional sensor with a global tridimensional map of the monitored volume stored in a memory,
• generate an aligned local point cloud from said acquired point cloud on the basis of the updated tridimensional position and orientation of the sensor, and
• monitor an intrusion in the monitored volume by comparing a free space of said aligned local point cloud with a free space of the global tridimensional map.