Dynamic scene prediction with multiple interacting agents
AssigneeNEC Laboratories America, Inc.
InventorsWongun Choi, Paul Vernaza, Manmohan Chandraker, Namhoon Lee
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Abstract
Methods and systems for predicting a trajectory include determining prediction samples for agents in a scene based on a past trajectory. The prediction samples are ranked according to a likelihood score that incorporates interactions between agents and semantic scene context. The prediction samples are iteratively refined using a regression function that accumulates scene context and agent interactions across iterations. A response activity is triggered when the prediction samples satisfy a predetermined condition.
Claims18
A method for predicting a trajectory, comprising:
- determining a plurality of prediction samples for agents in a scene based on a past trajectory;
- ranking the prediction samples using a processor according to a likelihood score that incorporates interactions between agents and semantic scene context;
- iteratively refining the prediction samples using a regression function that accumulates scene context and agent interactions across iterations;
- and
- triggering a response activity when the prediction samples satisfy a predetermined condition.
A system for predicting a trajectory, comprising:
- a prediction sample module configured to determine a plurality of prediction samples for agents in a scene based on a past trajectory;
- a ranking/refinement module comprising a processor configured to rank the prediction samples according to a likelihood score that incorporates interactions between agents and semantic scene context and to iteratively refine the prediction samples using a regression function that accumulates scene context and agent interactions across iterations;
- and
- a response module configured to trigger a response activity when the prediction samples satisfy a predetermined condition.
Dependencies are inferred from the claim text.