Systems and methods for coherent monitoring

1. A system for intelligently monitoring an environment, comprising: one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the system to:

obtain content representing an environment, the content comprising a plurality of frames, wherein the content comprises video content including the object captured from two angles;

identify, based on the content, one or more discrete objects observed within the environment;

track an object of the one or more discrete objects across the frames;

detect one or more events associated with the tracked object;

learn one or more patterns associated with the detected one or more events;

determine whether a second event deviates from the learned one or more patterns;

in response to determining that the second event deviates from the learned one or more patterns, flag the second event;

generate a three-dimensional (3D) model from the two angles of the object according to a 3D reconstruction algorithm; and

augment a map of the environment with the generated 3D model.

2. The system of claim 1 , wherein the learning the one or more patterns comprises learning seasonal changes in the one or more patterns.

3. The system of claim 1 , wherein the learning the one or more patterns associated with the detected one or more events comprises learning a range associated with the detected one or more events; and the determining whether a second event deviates from the learned one or more patterns comprises determining whether the second event is outside the range.

4. The system of claim 1 , wherein the memory stored instructions that, when executed by the one or more processors, further causes the system to:

present the map of the environment; and

simultaneously present a playback of the tracked object in a separate pane.

5. The system of claim 4 , wherein the memory stored instructions that, when executed by the one or more processors, further causes the system to:

identify a geographic boundary associated with the playback of the tracked object;

determine a corresponding boundary in the map;

detect an input to zoom in the geographic boundary; and

change the corresponding boundary in the map based on the input to zoom in.

6. The system of claim 1 , wherein the memory stored instructions that, when executed by the one or more processors, further causes the system to:

detect a number of occupants within the object based on a heat signature from thermal imagery; and

detect one or more attributes about an occupant of the occupants.

7. The system of claim 1 , wherein the detecting one or more events associated with the tracked object comprises:

detecting changes in the environment;

identifying candidate events based on the detected changes; and

comparing the candidate events with templates while accounting for a scaling, angle, or orientation difference between the object and corresponding objects in the templates.

8. The system of claim 1 , wherein the instructions further cause the system to:

determine a view field of a sensor capturing the content.

9. The system of claim 1 , wherein the instructions further cause the system to:

in response to detecting the one or more events, present a snapshot of a particular frame corresponding to the one or more detected events.

10. A method being implemented by a computing system including one or more physical processors and storage media storing machine-readable instructions, the method comprising:

obtaining content representing an environment, the content comprising a plurality of frames, wherein the content comprises video content including the object captured from two angles;

identifying, based on the content, one or more discrete objects observed within the environment;

tracking an object of the one or more discrete objects across the frames;

detecting one or more events associated with the tracked object;

learning one or more patterns associated with the detected one or more events;

determining whether a second event deviates from the learned one or more patterns;

in response to determining that the second event deviates from the learned one or more patterns, flagging the second event;

generate a three-dimensional (3D) model from the two angles of the object according to a 3D reconstruction algorithm; and

augment a map display of the environment with the generated 3D model.

11. The method of claim 10 , wherein the learning the one or more patterns comprises learning seasonal changes in the one or more patterns.

12. The method of claim 10 , wherein the learning the one or more patterns associated with the detected one or more events comprises learning a range associated with the detected one or more events; and the determining whether a second event deviates from the learned one or more patterns comprises determining whether the second event is outside the range.

13. The method of claim 10 , further comprising:

presenting the map of the environment; and

simultaneously presenting a playback of the tracked object in a separate pane.

14. The method of claim 13 , further comprising:

identifying a geographic boundary associated with the playback of the tracked object;

determining a corresponding boundary in the map;

detecting an input to zoom in the geographic boundary; and

changing the corresponding boundary in the map based on the input to zoom in.

15. The method of claim 10 , further comprising:

detecting a number of occupants within the object based on a heat signature from thermal imagery; and

detecting one or more attributes about an occupant of the occupants.

16. The method of claim 10 , wherein the detecting one or more events associated with the tracked object comprises:

detecting changes in the environment;

identifying candidate events based on the detected changes; and

comparing the candidate events with templates while accounting for a scaling, angle, or orientation difference between the object and corresponding objects in the templates.

17. A non-transitory computer readable medium comprising instructions that, when executed, cause one or more processors to perform:

obtaining content representing an environment, the content comprising a plurality of frames, wherein the content comprises video content including the object captured from two angles;

identifying, based on the content, one or more discrete objects observed within the environment;

tracking an object of the one or more discrete objects across the frames;

detecting one or more events associated with the tracked object;

learning one or more patterns associated with the detected one or more events;

determining whether a second event deviates from the learned one or more patterns; and

in response to determining that the second event deviates from the learned one or more patterns, flagging the second event;

generating a three-dimensional (3D) model from the two angles of the object according to a 3D reconstruction algorithm; and

augmenting the map of the environment with the generated 3D model.