公开(公告)号：US20220398294A1

公开(公告)日：2022-12-15

申请号：US17835343

申请日：2022-06-08

Applicant: SAAB AB

Inventor： Torbjörn Löfgren

IPC: G06F17/13

Abstract: The present disclosure relates to a computer-implemented method for object tracking, the method including the steps of defining a state-space of interest based on a class of objects subject to tracking. Further, the method includes the step of representing the state-space of interest using a FEM representation partitioning the state-space of interest in elements. Further, the method includes initiating a state-space distribution defining a probability density for different states of at least one tracked object in the state-space of interest. Moreover, the method updates the state-space distribution based on evidence, wherein the evidence being at least one of sensor data and external data of at least one tracked object in said class of objects. Furthermore, the method propagates the state-space distribution of the at least one tracked object for a time period.

公开(公告)号：US20220405942A1

公开(公告)日：2022-12-22

申请号：US17835357

申请日：2022-06-08

Applicant: SAAB AB

Inventor： Torbjörn Löfgren

IPC: G06T7/20

Abstract: The present disclosure relates to a computer-implemented method for object tracking applications, preferably in Bayesian object tracking applications. The method includes the steps of providing a finite element model representing a sensor model of at least one sensor. Further, the method trains said finite element model based on observations, wherein each observation includes an output of the at least one sensor paired with a known state of at least one training object, at the time of the output of the at least one sensor, in an environment sensed by the at least one sensor. Further, the method includes the steps of obtaining signals associated with at least one tracked object in an environment sensed by the at least one sensor. Furthermore, the method determines additional outputs of the at least one sensor based on the obtained signals.