Patent · US Active

Object behavior anomaly detection using neural networks

US11501572B2 · kind B2 · utility

0Cited by

9References

20Claims

0Family size

Assignee

NVIDIA Corporation · US

Inventors

Milind R. Naphade · Cupertino, US
Shuo Wang · Jinan, CN

Key dates

Filing date	Mar 25, 2019
Grant date	Nov 15, 2022
Priority date	—
Expiry date	Mar 28, 2039

Classification

Technology area (CPC G)Physics
CPC primaryG06V2201/08
WIPO fieldComputer technology
WIPO sectorElectrical engineering

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.