SYSTEM AND METHOD FOR GENERATING PLAYER TRACKING DATA FROM BROADCAST VIDEO

1 . A method, comprising:

identifying, by a computing system, a broadcast video feed for a sporting event, the broadcast video feed comprising a plurality of video frames;

segmenting, by the computing system, the broadcast video feed into a unified view, wherein the unified view comprises a plurality of trackable frames, the plurality of trackable frames is a subset of the plurality of video frames;

generating, by the computing system, body pose information for each player in each trackable frame of the plurality of trackable frames; and

constructing, by the computing system, future motion of a player based on the plurality of trackable frames and the body pose information.

2 . The method of claim 1 , wherein segmenting, by the computing system, the broadcast video feed into the unified view comprises:

parsing the broadcast video feed to identify a first subset of video frames corresponding to a same view of the sporting event; and

discarding a second subset of video frames corresponding to a different view of the sporting event.

3 . The method of claim 1 , further comprising:

identifying, by the computing system, a pattern of motion between two successive trackable frames by identifying players in each frame using the body pose information.

4 . The method of claim 3 , further comprising:

generating, by the computing system, a motion field vector for each player in the plurality of trackable frames.

5 . The method of claim 4 , wherein constructing, by the computing system, the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

generating, via a neural network, the future motion of the player based on the motion field vector generated for the player.

6 . The method of claim 1 , wherein constructing, by the computing system, the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

projecting motion of the player when the player has left a field of view and is not visible in the broadcast video feed.

7 . The method of claim 6 , wherein projecting the motion of the player when the player has left a field of view and is not visible in the broadcast video feed comprises:

identifying a first set of frames in which the player is present;

identifying a second set of frames following the first set of frames in which the player is not present; and

predicting a trajectory of the player based on prior trajectories of the player in the first set of frames.

8 . A system for generating a player tracking prediction, comprising:

a processor; and

a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform one or more operations comprising:

identifying a broadcast video feed for a sporting event, the broadcast video feed comprising a plurality of video frames;

segmenting the broadcast video feed into a unified view, wherein the unified view comprises a plurality of trackable frames, the plurality of trackable frames is a subset of the plurality of video frames;

generating body pose information for each player in each trackable frame of the plurality of trackable frames; and

constructing future motion of a player based on the plurality of trackable frames and the body pose information.

9 . The system of claim 8 , wherein segmenting the broadcast video feed into the unified view comprises:

parsing the broadcast video feed to identify a first subset of video frames corresponding to a same view of the sporting event; and

discarding a second subset of video frames corresponding to a different view of the sporting event.

10 . The system of claim 8 , wherein the one or more operations further comprise:

identifying a pattern of motion between two successive trackable frames by identifying players in each frame using the body pose information.

11 . The system of claim 10 , wherein the one or more operations further comprise:

generating a motion field vector for each player in the plurality of trackable frames.

12 . The system of claim 11 , wherein constructing the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

generating, via a neural network, the future motion of the player based on the motion field vector generated for the player.

13 . The system of claim 8 , wherein constructing the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

projecting motion of the player when the player has left a field of view and is not visible in the broadcast video feed.

14 . The system of claim 13 , wherein projecting the motion of the player when the player has left a field of view and is not visible in the broadcast video feed comprises:

identifying a first set of frames in which the player is present;

identifying a second set of frames following the first set of frames in which the player is not present; and

predicting a trajectory of the player based on prior trajectories of the player in the first set of frames.

15 . A non-transitory computer readable medium including one or more sequences of instructions that, when executed by one or more processors, causes a computing system to perform one or more operations comprising:

identifying, by the computing system, a broadcast video feed for a sporting event, the broadcast video feed comprising a plurality of video frames;

segmenting, by the computing system, the broadcast video feed into a unified view, wherein the unified view comprises a plurality of trackable frames, the plurality of trackable frames is a subset of the plurality of video frames;

generating, by the computing system, body pose information for each player in each trackable frame of the plurality of trackable frames; and

constructing, by the computing system, future motion of a player based on the plurality of trackable frames and the body pose information.

16 . The non-transitory computer readable medium of claim 15 , wherein segmenting, by the computing system, the broadcast video feed into the unified view comprises:

parsing the broadcast video feed to identify a first subset of video frames corresponding to a same view of the sporting event; and

discarding a second subset of video frames corresponding to a different view of the sporting event.

17 . The non-transitory computer readable medium of claim 15 , further comprising:

identifying, by the computing system, a pattern of motion between two successive trackable frames by identifying players in each frame using the body pose information.

18 . The non-transitory computer readable medium of claim 17 , further comprising:

generating, by the computing system, a motion field vector for each player in the plurality of trackable frames.

19 . The non-transitory computer readable medium of claim 18 , wherein constructing, by the computing system, the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

generating, via a neural network, the future motion of the player based on the motion field vector generated for the player.

20 . The non-transitory computer readable medium of claim 15 , wherein constructing, by the computing system, the future motion of the player based on the plurality of trackable frames and the body pose information comprises:

projecting motion of the player when the player has left a field of view and is not visible in the broadcast video feed.