SYSTEM AND METHOD FOR PREDICTING FINE-GRAINED ADVERSARIAL MULTI-AGENT MOTION
A system and method for predicting multi-agent locations is disclosed herein. A computing system retrieves tracking data from a data store. The computing system generates a predictive model using a conditional variational autoencoder. The conditional variational autoencoder learns one or more paths a subset of agents of the plurality of agents are likely to take. The computing system receives tracking data from a tracking system positioned remotely in a venue hosting a candidate sporting event. The computing system identifies one or more candidate agents for which to predict locations. The computing system infers, via the predictive model, one or more locations of the one or more candidate agents. The computing system generates a graphical representation of the one or more locations of the one or more candidate agents.
1 . A method of predicting multi-player location, comprising:
receiving, by a computing system, tracking data from a tracking system positioned remotely in a venue hosting a sporting event, the tracking data comprising coordinate data for a plurality of sequences of movements for a first plurality of players on a playing surface during the sporting event;
identifying, by the computing system, a second plurality of players of players co-located with the first plurality of players on the playing surface;
accessing, by the computing system, identity information for each player of the first plurality of players and the second plurality of players, the identity information comprising at least one of name, team, or position;
projecting, via an autoencoder of the computing system, a future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface; and
generating, by the computing system, a graphical representation of the future location of each player on the playing surface.
2 . The method of claim 1 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on learned trajectories of the first plurality of players.
3 . The method of claim 1 , further comprising:
encoding, by the autoencoder, each player's sequence of movements using an encoder of the autoencoder.
4 . The method of claim 1 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based an identity of a team comprising the first plurality of players.
5 . The method of claim 1 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on identities of each player of the first plurality of players.
6 . The method of claim 1 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on a current context of the sporting event.
7 . The method of claim 1 , wherein generating, by the computing system, the graphical representation of the future location of each player on the playing surface comprises:
generating a first graphical representation of the plurality of sequences of movements for the first plurality of players; and
generating a second graphical representation of a second plurality of future sequences of movements for the first plurality of players based on the projected future location of each player; and
appending the first graphical representation with the second graphical representation corresponding to each player.
8 . A non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by a processor, causes a computing system to perform operations comprising:
receiving, by the computing system, tracking data from a tracking system positioned remotely in a venue hosting a sporting event, the tracking data comprising coordinate data for a plurality of sequences of movements for a first plurality of players on a playing surface during the sporting event;
identifying, by the computing system, a second plurality of players of players co-located with the first plurality of players on the playing surface;
accessing, by the computing system, identity information for each player of the first plurality of players and the second plurality of players, the identity information comprising at least one of name, team, or position;
projecting, via an autoencoder of the computing system, a future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface; and
generating, by the computing system, a graphical representation of the future location of each player on the playing surface.
9 . The non-transitory computer readable medium of claim 8 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on learned trajectories of the first plurality of players.
10 . The non-transitory computer readable medium of claim 8 , further comprising:
encoding, by the autoencoder, each player's sequence of movements using an encoder of the autoencoder.
11 . The non-transitory computer readable medium of claim 8 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based an identity of a team comprising the first plurality of players.
12 . The non-transitory computer readable medium of claim 8 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on identities of each player of the first plurality of players.
13 . The non-transitory computer readable medium of claim 8 , wherein projecting, via the autoencoder of the computing system, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on a current context of the sporting event.
14 . The non-transitory computer readable medium of claim 8 , wherein generating, by the computing system, the graphical representation of the future location of each player on the playing surface comprises:
generating a first graphical representation of the plurality of sequences of movements for the first plurality of players; and
generating a second graphical representation of a second plurality of future sequences of movements for the first plurality of players based on the projected future location of each player; and
appending the first graphical representation with the second graphical representation corresponding to each player.
15 . A system, comprising:
a processor; and
a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform operations comprising:
receiving tracking data from a tracking system positioned remotely in a venue hosting a sporting event, the tracking data comprising coordinate data for a plurality of sequences of movements for a first plurality of players on a playing surface during the sporting event;
identifying a second plurality of players of players co-located with the first plurality of players on the playing surface;
accessing identity information for each player of the first plurality of players and the second plurality of players, the identity information comprising at least one of name, team, or position;
projecting, via an autoencoder, a future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface; and
generating a graphical representation of the future location of each player on the playing surface.
16 . The system of claim 15 , wherein projecting, via the autoencoder, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on learned trajectories of the first plurality of players.
17 . The system of claim 15 , wherein projecting, via the autoencoder, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based an identity of a team comprising the first plurality of players.
18 . The system of claim 15 , wherein projecting, via the autoencoder, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on identities of each player of the first plurality of players.
19 . The system of claim 15 , wherein projecting, via the autoencoder, the future location of each player of the first plurality of players based on each player's sequence of movements and the second plurality of players co-located with the first plurality of players on the playing surface further comprises:
projecting, via the autoencoder, the future location of each player of the first plurality of players based on a current context of the sporting event.
20 . The system of claim 15 , wherein generating the graphical representation of the future location of each player on the playing surface comprises:
generating a first graphical representation of the plurality of sequences of movements for the first plurality of players; and
generating a second graphical representation of a second plurality of future sequences of movements for the first plurality of players based on the projected future location of each player; and
appending the first graphical representation with the second graphical representation corresponding to each player.