TRAVELING IN TIME AND SPACE CONTINUUM

1 . A computer-implemented method for remote viewing, the computer-implemented method comprising:

obtaining a sequence of images of a location, wherein the sequence of images is captured by at least one of a plurality of cameras positioned at one or more positions in the location;

generating a virtual space, wherein the virtual space is a virtual representation of the location;

determining at least one of a position, a direction of travel, or a speed of travel of a remote user within the virtual representation of the location based on one or more measurements obtained from a sensory input from the remote user;

selecting a subset of cameras from the plurality of cameras positioned at one or more positions in the location based on at least one of the position, the direction of travel, or the speed of travel of the user within the virtual representation of the location; and

causing a user device located at the remote location of the remote user to display one or more images in the sequence of images captured by the subset of cameras in an order based on the position, the direction of travel, and the speed of travel of the user within the virtual representation of the location.

2 . The computer-implemented method of claim 1 , further comprising:

receiving an indication of an object to track and a first image in the sequence of images captured by a first camera in the subset of cameras and displayed by the user device;

applying image processing to the first image to identify a characteristic of the object;

applying image processing to images in the sequence of images other than the first image to identify a second image in the sequence of images that depicts the object with the characteristic; and

causing the user device to display the second image following the first image.

3 . The computer-implemented method of claim 2 , wherein applying image processing to the first image further comprises applying the first image as an input to a trained object detection artificial intelligence model, wherein applying the first image as the input to the trained object detection artificial intelligence model causes the trained object detection artificial intelligence model to output an indication that the object with the characteristic is depicted in the first image.

4 . The computer-implemented method of claim 1 , wherein causing a user device to display one or more images in the sequence of images captured by the subset of cameras in an order based on the position, the direction of travel, and the speed of travel of the user within the virtual representation of the location further comprises:

determining a location of a first camera in the subset of cameras that captured a first image in the sequence of images that is displayed by the user device;

determining a distance from the first camera based on at least one of the direction of travel of the user or the speed of travel of the user;

determining that a second camera in the subset of cameras is located at a distance from the location of the first camera that matches the determined distance; and

causing the user device to display a second image in the sequence of images captured by the second camera subsequent to the user device displaying the first image.

5 . The computer-implemented method of claim 1 , wherein the sensory input comprises one of a touch input, a haptic input, a gesture input, a wearable input, or a voice input provided to the user device.

6 . The computer-implemented method of claim 1 , further comprising determining at least one of an updated position, an updated direction of travel, or an updated speed of a travel of the user within the virtual representation of the location based on one or more second measurements obtained from the sensory input and generated subsequent to the one or more measurements.

7 . The computer-implemented method of claim 1 , wherein each camera in the plurality of cameras is spaced evenly throughout the location.

8 . The computer-implemented method of claim 1 , wherein at least some cameras in the plurality of cameras are spaced unevenly throughout the location.

9 . The computer-implemented method of claim 1 , wherein the one or more images captured by the subset of cameras are displayed by the user device within a threshold time of the one or more images being captured by the subset of cameras.

10 . The computer-implemented method of claim 1 , wherein the one or more images captured by the subset of cameras are displayed by the user device at a rate that is slower than a rate at which the one or more images are captured by the subset of cameras.

11 . The computer-implemented method of claim 1 , wherein the one or more images captured by the subset of cameras are displayed by the user device at a rate that is faster than a rate at which the one or more images are captured by the subset of cameras.

12 . The computer implemented method of claim 1 , wherein causing a user device to display one or more images in the sequence of images captured by the subset of cameras in an order based on the position, the direction of travel, and the speed of travel of the user within the virtual representation of the location further comprises:

determining a location of a first camera in the subset of cameras that captured a first image in the sequence of images that is displayed by the user device;

determining a first position from the first camera based on at least one of the direction of travel of the user or the speed of travel of the user;

determining that a second camera in the subset of cameras is located at a second position from the location of the first camera, wherein the second position's distance is greater from the position of the first camera than the first position, wherein the second camera is closest in location to the first position;

generating a pixel-averaged frame; and

causing the user device to display the pixel-averaged frame in the sequence of images subsequent to the user device displaying the first image.

13 . The computer implemented method of claim 12 , wherein the step of generating a pixel-averaged frame comprises:

retrieving one or more picture frames each from the first camera and the second camera; and

averaging RGB values of one or more pixels comprising the one or more picture frames at corresponding relative coordinate positions from the one or more picture frames to generate the pixel-averaged frame.

14 . The computer implemented method of claim 13 , wherein averaging RGB values of one or more pixels comprises:

determining the individual red, green, and blue values of the one or more pixels comprising the one or more picture frames,

determining an average red, green, and blue values for each of the one or more pixels, thereby generating an averaged pixel for each of the one or more pixels and generating the pixel averaged frame by positioning the averaged pixel for each of the one or more pixels.

15 . The computer implemented method of claim 13 , wherein there are no intervening cameras located between the positions of the first and the second cameras.

16 . The computer implemented method of claim 13 , wherein the pixel averaged frame approximates a view generated by a virtual third camera located in between the positions of the first and second cameras, wherein the virtual third camera is not present between the positions of the first and second cameras, wherein the virtual third camera is located at the first position.

17 . The computer implemented method of claim 13 , wherein the pixel averaged frame is image corrected before causing the user device to display the pixel-averaged frame, wherein image correction comprises one or more of: distortion correction, perspective correction, or angle-distortion correction.