Real-time stadiametric ranging

1 . A method for displaying real time stadiametric range finding via an optic device, the method comprising:

receiving digital image data captured by one or more image capture devices;

detecting at least one object in the digital image data using at least one machine learning model;

determining a confidence level indicating a confidence of object detection performed by the at least one machine learning model;

transforming the at least one detected object into graphical markup data and identification data;

correlating the identification data with stored physical properties of one or more object types, including obtaining an average height physical property associated with a type of the at least one detected object from a database;

determining a minute of angle (MOA) that a pixel of a display of the optic device represents;

calculating a distance to the at least one detected object using correlated object properties and image capture device properties including the MOA that a pixel of the display represents, including calculating an estimated range from the optic device to the at least one detected object based on the average height physical property and a height of the at least one detected object in the digital image data;

displaying the calculated distance, confidence level and graphical object markup cues on the display of the optic device; and

displaying a corrected reticle on the display of the optic device, wherein the corrected reticle is positioned based on the correlated object properties of the at least one detected object and the calculated distance to the at least one detected object.

2 . The method of claim 1 , wherein the one or more image capture devices include at least one of a lens of the optic device or an imager of the optic device.

3 . The method of claim 1 , wherein the digital image data captured by the one or more image capture devices includes image data captured via at least one of multiple image capture angles, multiple image capture wavelengths, multiple image capture bit depths, and multiple image capture resolutions.

4 . The method of claim 1 , wherein detecting at least one object includes applying an object detection algorithm to the digital image data.

5 . The method of claim 4 , wherein the object detection algorithm includes at least one of normalized correlation, feature-based pattern matching, or a convolutional neural network (CNN).

6 . The method of claim 1 , wherein transforming the at least one detected object includes generating graphical outline data to highlight the at least one detected object on the display of the optic device.

7 . The method of claim 1 , wherein the identification data includes at least one of an identification of the at least one detected object, a placement location of the at least one detected object, or an orientation of the at least one detected object.

8 . The method of claim 1 , wherein:

the database is configured to store physical properties of multiple object types; and

correlating the identification data includes matching the identification data with the stored physical properties of the multiple object types, to select a strongest match between the identification data associated with the at least one detected object and the stored physical properties of at least one of the multiple object types.

9 . The method of claim 8 , wherein the stored physical properties include at least one of a minimum height of each object type, a maximum height of each object type, an average height of each object type, a minimum area of each object type, a maximum area of each object type, or average area of each object type.

10 . The method of claim 1 , wherein calculating the distance includes calculating an estimated range from the optic device to the at least one detected object based on at least one of a correlated area of the at least one detected object, or an orientation of the at least one detected object.

11 . The method of claim 10 , wherein calculating the distance includes calculating the estimated range according to at least one physical property of the one or more image capture devices.

12 . The method of claim 11 , wherein the at least one physical property includes at least one of a focal length of the one or more image capture devices, a field of view of the one or more image capture devices, or a focal plane geometry of the one or more image capture devices.

13 . The method of claim 1 , wherein displaying the calculated distance includes updating graphics of the display of the optic device to display at least one of a highlight of the at least one detected object, an estimated range of the at least one detected object, and a description of the at least one detected object.

14 . The method of claim 1 , wherein displaying the calculated distance includes displaying two estimated ranges, each estimated range corresponding to a different detected object.

15 . The method of claim 1 , further comprising:

detecting a second object in the digital image data using the at least one machine learning model; and

displaying an updated corrected reticle on the display associated with the second object, in response to movement of the optic device to move an uncorrected reticle over the second object.

16 . An optic device comprising:

a lens;

an imager configured to capture digital image data via the lens;

a display configured to display images to a user;

memory configured to store physical properties of one or more object types, and computer-executable instructions; and

at least one processor configured to execute the computer-executable instructions to:

receive the digital image data captured by the imager;

detect at least one object in the digital image data using at least one machine learning model;

determine a confidence level indicating a confidence of object detection performed by the at least one machine learning model;

transform the at least one detected object into graphical markup data and identification data;

correlate the identification data with the physical properties of one or more object types stored in the memory, including obtaining an average height physical property associated with a type of the at least one detected object from memory;

determine a minute of angle (MOA) that a pixel of the display of the optic device represents;

calculate a distance to the at least one detected object using correlated object properties and image capture device properties including the MOA that a pixel of the display represents, including calculating an estimated range from the optic device to the at least one detected object based on the average height physical property and a height of the at least one detected object in the digital image data;

display the calculated distance, confidence level and graphical object markup cues on the display of the optic device; and

display a corrected reticle on the display of the optic device, wherein the corrected reticle is positioned based on the correlated object properties of the at least one detected object and the calculated distance to the at least one detected object.

17 . The optic device of claim 16 , wherein the digital image data captured by the imager includes image data captured via at least one of multiple image capture angles, multiple image capture wavelengths, multiple image capture bit depths, and multiple image capture resolutions.

18 . The optic device of claim 16 , wherein:

detecting at least one object includes applying an object detection algorithm to the digital image data; and

the object detection algorithm includes at least one of normalized correlation, feature-based pattern matching, or a convolutional neural network (CNN).

19 . The optic device of claim 16 , wherein transforming the at least one detected object includes generating graphical outline data to highlight the at least one detected object on the display of the optic device.

20 . The optic device of claim 16 , wherein the identification data includes at least one of an identification of the at least one detected object, a placement location of the at least one detected object, an orientation of the at least one detected object, a disturbed reticle location associated with the at least one detected object, or a shot correction reference associated with the at least one detected object.