USER ANALYTICS USING A CAMERA DEVICE AND ASSOCIATED SYSTEMS AND METHODS
Methods and systems for performing a location determination in a three-dimensional environment using a computing device with a camera are disclosed. The methods and systems perform the steps of receiving an image of a user from the camera of the computing device. Identifying the user from the image using a first algorithm, where the first algorithm is a machine learning algorithm. Determining a pose information associated with the user using a second algorithm, where the second algorithm is a machine vision algorithm. Determining a depth information associated with the user based on the pose information and an input parameter (e.g., height) of the user using a search process (e.g., binary search). Finally, determining the location of the user in the environment based on the pose information and the depth information.
1 . A computer-implemented method for performing a location determination in a three-dimensional environment, comprising:
receiving an image of a user from a camera of a computing device;
identifying the user from the image using a first algorithm, wherein the first algorithm is a machine learning algorithm;
determining a pose information associated with the user using a second algorithm, wherein the second algorithm is a machine vision algorithm;
determining a depth information associated with the user based on the pose information and an input parameter of the user using a search process; and
determining the location of the user in the three-dimensional environment based on the pose information and the depth information.
2 . The computer-implemented method of claim 1 , wherein the depth information comprises a depth of the user with respect to the camera.
3 . The computer-implemented method of claim 2 , further comprising:
determining a first pose size of the user from a first user pose;
determining a second pose size of the user from a second user pose; and
determining the depth information based on one or more of the camera's center, a distance to an imaging plane, an input height of the user, the first pose size, and the second pose size.
4 . The computer-implemented method of claim 3 , further comprising:
determining the first pose size based on a length of pose limbs associated with the first user pose.
5 . The computer-implemented method of claim 1 , further comprising:
determining a movement associated with the user based on the pose information.
6 . The computer-implemented method of claim 1 , further comprising:
determining a direction of gravity using the computing device;
determining a second location of a portion of the user's body in the three-dimensional environment; and
determining, based on the second location, a distance between the camera and the second location.
7 . The computer-implemented method of claim 6 , further comprising:
determining, based on the depth information, a reference plane in the camera's coordinate system.
8 . The computer-implemented method of claim 1 , wherein the pose information comprises noisy pose data, and the computer-implemented method further comprises:
applying a filter to the noisy pose data; and
determining a second location of the user based on the filtered noisy pose data, wherein the second location has a greater accuracy than the location.
9 . The computer-implemented method of claim 1 , wherein the input parameter of the user is the user's height.
10 . The computer-implemented method of claim 1 , wherein the search process is a binary search process.
11 . One or more non-transitory storage media for performing a location determination in a three-dimensional environment, the non-transitory storage medium comprising machine-readable program code that cause a processor to:
receive an image of a user from a camera of a computing device;
identify the user from the image using a first algorithm, wherein the first algorithm is a machine learning algorithm;
determine a pose information associated with the user using a second algorithm, wherein the second algorithm is a machine vision algorithm;
determine a depth information associated with the user based on the pose information and an input parameter of the user using a search process; and
determine the location of the user in the three-dimensional environment based on the pose information and the depth information.
12 . The one or more non-transitory storage media of claim 11 , further comprising program code to:
determine a first pose size of the user from a first user pose;
determine a second pose size of the user from a second user pose; and
determine the depth information based on one or more of the camera's center, a distance to an imaging plane, an input height of the user, the first pose size, and the second pose size.
13 . The one or more non-transitory storage media of claim 11 , further comprising program code to:
determine a direction of gravity using the computing device;
determine a second location of a portion of the user's body in the three-dimensional environment; and
determine, based on the second location, a distance between the camera and the second location.
14 . The one or more non-transitory storage media of claim 11 , wherein the input parameter of the user is the user's height.
15 . The one or more non-transitory storage media of claim 11 , wherein the search process is a binary search process.
16 . A computing device for performing a location determination in a three-dimensional environment, comprising:
a camera device;
a processor; and
a memory storing program code thereon, the program code executable by the processor to:
receive an image of a user from the camera device of the computing device;
identify the user from the image using a first algorithm, wherein the first algorithm is a machine learning algorithm;
determine a pose information associated with the user using a second algorithm, wherein the second algorithm is a machine vision algorithm;
determine a depth information associated with the user based on the pose information and an input parameter of the user using a search process; and
determine the location of the user in the three-dimensional environment based on the pose information and the depth information.
17 . The computing device of claim 16 , further comprising program code to:
determine a first pose size of the user from a first user pose;
determine a second pose size of the user from a second user pose; and
determine the depth information based on one or more of the camera's center, a distance to an imaging plane, an input height of the user, the first pose size, and the second pose size.
18 . The computing device of claim 16 , further comprising program code to:
determine a direction of gravity using the computing device;
determine the location of a portion of the user's body in the three-dimensional environment; and
determine, based on the location, a distance between the camera and the location.
19 . The computing device of claim 16 , wherein the input parameter of the user is the user's height.
20 . The computing device of claim 16 , wherein the search process is a binary search process.