Remote multiplayer interactive physical gaming with mobile computing devices
Methods and systems for remote multiplayer gameplay are disclosed. An example method can include joining a multiplayer interactive physical game including first and second players competing in an activity; capturing a first game video of a first player in a first play of the multiplayer interactive physical game, using a first camera on a first mobile computing device in a first gaming area; determining a first object flow associated with the first player from the first game video, by performing an algorithm on one or more frames of the first game video to detect one or more key points of the first player; generating a first analytic based on the first object flow; receiving a second analytic associated with the second player in a second gaming area; and generating a feedback to the first player based on the first analytic or the second analytic.
1. A method for physical gaming with a mobile computing device, comprising:
joining a game comprising at least a player;
capturing a video of the player in the game using a camera of the mobile computing device;
determining an object flow associated with the player from the video by detecting one or more key points of the player using a machine learning technique for performing at least one of an object recognition, a pose estimation, and an object flow construction on the video;
determining an affinity field map using the machine learning technique; and
determining a pose of the player based on the key points and the affinity field map.
2. The method of claim 1 , wherein the player comprises a first player, the game comprises a second player, the object flow comprises a first object flow, and the method further comprises:
generating a first analytic based on the first object flow;
receiving a second analytic associated with the second player; and
generating a feedback to the first player based on at least one of the first analytic and the second analytic.
3. The method of claim 1 , wherein the player comprises a first player, the game comprises a second player, and wherein the first player is located in a first gaming area and the second player is located in a second gaming area geographically different from the first gaming area.
4. The method of claim 1 , wherein the player comprises a first player, the game comprises a second player, and wherein the first player and the second player of the game are playing asynchronously in time.
5. The method of claim 1 , further comprising:
receiving a user input, at the mobile computing device, from the player to initiate the game.
6. The method of claim 1 , further comprising:
detecting a scoring attempt from the video and generating a first analytic based on the scoring attempt.
7. The method of claim 1 , further comprising:
generating an analytic based on the object flow; and generating a feedback based on the analytic.
8. The method of claim 7 , further comprising:
providing the feedback to the player using at least one of an audio output and a video output associated with the mobile computing device.
9. The method of claim 7 , wherein the feedback comprises instructions for the player.
10. The method of claim 7 , further comprising:
determining a location of a portion of a body of the player from the video, wherein the generating the feedback is further based on the location.
11. A system for physical gaming with a mobile computing device, comprising:
at least one processor; and
a non-transitory physical medium for storing program code accessible by the at least one processor, the program code when executed by the processor causing the processor to:
join a game comprising at least a player;
capture a video of the player in the game using a camera of the mobile computing device;
determine an object flow associated with the player from the video by detecting one or more key points of the player using a machine learning technique for performing at least one of an object recognition, a pose estimation, and an object flow construction on the video;
determine an affinity field map using the machine learning technique; and
determine a pose of the player based on the key points and the affinity field map.
12. The system of claim 11 , wherein the player comprises a first player, the game comprises a second player, the object flow comprises a first object flow, and the program code causes the processor to further:
generate a first analytic based on the first object flow;
receive a second analytic associated with the second player; and
generate a feedback to the first player based on at least one of the first analytic and the second analytic.
13. The system of claim 11 , wherein the player comprises a first player, the game comprises a second player, and wherein the first player is located in a first gaming area and the second player is located in a second gaming area geographically different from the first gaming area.
14. The system of claim 11 , wherein the player comprises a first player, the game comprises a second player, and wherein the first player and the second player of the game are playing asynchronously in time.
15. The system of claim 11 , wherein the program code causes the processor to further:
receive a user input, at the mobile computing device, from the player to initiate the game.
16. The system of claim 11 , wherein the program code causes the processor to further:
detect a scoring attempt from the video and generate a first analytic based on the scoring attempt.
17. The system of claim 11 , wherein the program code causes the processor to further:
generate an analytic based on the object flow; and generate a feedback based on the analytic.
18. The system of claim 17 , wherein the program code causes the processor to further:
provide the feedback to the player using at least one of an audio output and a video output associated with the mobile computing device.
19. The system of claim 17 , wherein the program code causes the processor to further:
determine a location of a portion of a body of the player from the video, wherein the program code to generate the feedback is further based on the location.
20. A non-transitory physical storage medium for physical gaming with a mobile computing device, the storage medium comprising program code stored thereon, the program code when executed by a processor causing the processor to:
join a game comprising at least a player;
capture a video of the player in the game using a camera of the mobile computing device;
determine an object flow associated with the player from the video by detecting one or more key points of the player using a machine learning technique for performing at least one of an object recognition, a pose estimation, and an object flow construction on the video;
determine an affinity field map using the machine learning technique; and
determine a pose of the player based on the key points and the affinity field map.