Object movement behavior learning
AssigneeNVIDIA Corporation
InventorsMilind Naphade, Shuo Wang
Life of this patent
Estimating the term…
Abstract
In various examples, a set of object trajectories may be determined based at least in part on sensor data representative of a field of view of a sensor. The set of object trajectories may be applied to a long short-term memory (LSTM) network to train the LSTM network. An expected object trajectory for an object in the field of view of the sensor may be computed by the LSTM network based at least in part an observed object trajectory. By comparing the observed object trajectory to the expected object trajectory, a determination may be made that the observed object trajectory is indicative of an anomaly.
Claims20
A method comprising:
- determining an object trajectory including at least one series of first positions of one or more objects in an environment;
- determining, using one or more portions of the object trajectory, a plurality of predicted object trajectories associated with the object trajectory, the plurality of predicted object trajectories computed using at least one machine learning model;
- identifying, for respective trajectories of the plurality of predicted object trajectories, respective deviations from the object trajectory based at least on differences between a series of positions along the object trajectory and at least two other series of positions along the plurality of predicted object trajectories;
- determining an anomaly between the object trajectory and the respective trajectories based at least on a value aggregated from individual contributions of the respective deviations for the respective trajectories exceeding a threshold;
- and
- generating one or more notifications indicative of the anomaly.
A system comprising:
- one or more processing units to perform operations including:
- determining an object trajectory including at least one series of first positions of one or more objects in an environment;
- determining, using one or more portions of the object trajectory, a plurality of predicted object trajectories associated with the object trajectory, the plurality of predicted object trajectories computed using at least one machine learning model;
- comparing the object trajectory to the plurality of predicted object trajectories to identify, for respective trajectories of the plurality of predicted object trajectories, respective deviations between the object trajectory and the respective trajectories;
- determining an anomaly between the object trajectory and the respective trajectories based at least on a value aggregated from individual contributions of the respective deviations for the respective trajectories exceeding a threshold;
- and
- generating one or more notifications indicative of the anomaly.
At least one processor comprising:
- one or more circuits to generate one or more notifications based at least on:
- determining, using one or more portions of an object trajectory, a plurality of predicted object trajectories associated with the object trajectory, the plurality of predicted object trajectories computed using at least one machine learning model,
- identifying, for respective trajectories of the plurality of predicted object trajectories, respective deviations from the object trajectory based at least on differences between the object trajectory and the respective trajectories, and
- determining an anomaly between the object trajectory and the respective trajectories based at least on a value aggregated from individual contributions of the respective deviations for the respective trajectories exceeding a threshold.
Dependencies are inferred from the claim text.