Systems and methods for recommending content items based on an identified posture

1. A method for generating a content item recommendation based on an identified posture, the method comprising:

receiving, at a computing device, an input associated with a content item delivery service;

receiving a capture of a user;

generating, based on the capture of the user, a digital representation of the user;

determining, based on the digital representation of the user, a posture of the user;

identifying, based on the determined posture of the user, a known posture that most closely matches the determined posture of the user;

identifying, based on the known posture, a content item genre;

generating, based on the identified genre, a content item recommendation; and

outputting the generated content item recommendation.

2. The method of claim 1 , further comprising determining an emotion of the user, wherein the content item genre is further determined based on the determined emotion.

3. The method of claim 1 , further comprising:

determining a time period associated with the identified posture;

identifying whether the time period exceeds a threshold time period; and, if the time period exceeds the threshold time period:

identifying, based on the determined posture of the user and the time period, an updated content item genre;

generating, based on the updated content item genre, an updated content item recommendation; and

outputting the updated content item recommendation.

4. The method of claim 1 , further comprising identifying an orientation of the computing device, wherein determining the posture of the user further comprises determining a posture based on the identified orientation of the computing device.

5. The method of claim 1 , wherein identifying a content item genre further comprises determining a genre via a posture-to-genre mapping table.

6. The method of claim 5 , further comprising:

identifying an interaction level associated with a content item recommendation;

determining whether the interaction level is below a threshold value; and, if the interaction level is below the threshold value:

updating the posture-to-genre mapping table to associate a different posture with the genre on which the content item recommendation has been generated.

7. The method of claim 1 , wherein:

the capture is of a plurality of users;

generating the digital representation of the user further comprises generating a digital representation of at least a subset of the plurality of users; and the method further comprises:

identifying at least a subset of the users in the digital representation;

generating a probability value associated with each user of the plurality of users, wherein the probability value indicates a probability of each user interacting with the service; and wherein:

the posture is identified for the user having the highest probability value associated with them.

8. The method of claim 7 , wherein the at least a subset of users in the digital representation are identified via silhouette-based feature extraction.

9. The method of claim 1 , wherein the input is spoken input, and the method further comprises:

identifying a user profile based on the spoken input; and

associating the determined posture with the user profile.

10. The method of claim 1 , further comprising:

receiving, at the computing device, a segment of a content item and an associated manifest file;

identifying, via the manifest file, an indication to determine the posture of the user at a playback time of the content item; and wherein:

determining the posture of the user further comprises determining the posture of the user at the indicated playback time.

11. A system for generating a content item recommendation based on an identified posture, the system comprising:

a communication port;

a memory storing instructions; and

control circuitry communicably coupled to the memory and the communication port and configured to execute instructions to:

receive, at a computing device, an input associated with a content item delivery service;

receive a capture of a user;

generate, based on the capture of the user, a digital representation of the user;

determine, based on the digital representation of the user, a posture of the user;

identify, based on the determined posture of the user, a known posture that most closely matches the determined posture of the user;

identify, based on the known posture, a content item genre;

generate, based on the identified genre, a content item recommendation; and

output the generated content item recommendation.

12. The system of claim 11 , further comprising control circuitry configured to determine an emotion of the user, and wherein the control circuitry configured to determine the content item genre is further configured to determine the content item genre based on the determined emotion.

13. The system of claim 11 , further comprising control circuitry configured to:

determine a time period associated with the identified posture;

identify whether the time period exceeds a threshold time period; and, if the time period exceeds the threshold time period:

identify, based on the determined posture of the user and the time period, an updated content item genre;

generate, based on the updated content item genre, an updated content item recommendation; and

output the updated content item recommendation.

14. The system of claim 11 , further comprising control circuitry configured to identify an orientation of the computing device, and wherein the control circuitry configured to determine the posture of the user is further configured to determine a posture based on the identified orientation of the computing device.

15. The system of claim 11 , wherein the control circuitry configured to identify a content item genre is further configured to determine a genre via a posture-to-genre mapping table.

16. The system of claim 15 , further comprising control circuitry configured to:

identify an interaction level associated with a content item recommendation;

determine whether the interaction level is below a threshold value; and, if the interaction level is below the threshold value:

update the posture-to-genre mapping table to associate a different posture with the genre on which the content item recommendation has been generated.

17. The system of claim 11 , wherein:

the capture is of a plurality of users;

the control circuitry configured to generate the digital representation of the user is further configured to generate a digital representation of at least a subset of the plurality of users; and

the control circuitry is further configured to:

identify at least a subset of the users in the digital representation;

generate a probability value associated with each user of the plurality of users, wherein the probability value indicates a probability of each user interacting with the service; and wherein:

the control circuitry configured to identify a posture is further configured to identify a posture for the user having the highest probability value associated with them.

18. The system of claim 17 , wherein the control circuitry configured to identify the at least a subset of the users in the digital representation is further configured to identify the users via silhouette-based feature extraction.

19. The system of claim 11 , wherein the control circuitry configured to receive the input is further configured to receive spoken input, and the control circuitry is further configured to:

identify a user profile based on the spoken input; and

associate the determined posture with the user profile.

20. The system of claim 11 , further comprising control circuitry configured to:

receive, at the computing device, a segment of a content item and an associated manifest file;

identify, via the manifest file, an indication to determine the posture of the user at a playback time of the content item; and wherein:

the control circuitry configured to determine the posture of the user is further configured to determine the posture of the user at the indicated playback time.