公开(公告)号：US20240257372A1

公开(公告)日：2024-08-01

申请号：US18456170

申请日：2023-08-25

申请人： KABUSHIKI KAISHA TOSHIBA

发明人： Atsushi KAWASAKI ,  Tomoki WATANABE

IPC分类号： G06T7/564 ,  G06T7/73 ,  G06T17/00

CPC分类号： G06T7/564 ,  G06T7/75 ,  G06T17/00 ,  G06T2207/10028 ,  G06T2207/30256 ,  G06T2210/56

摘要： A computer program product includes a computer-readable recording medium on which programmed instructions causing a computer to perform the following processing are recorded. The computer specifies a reference coordinate system of a three-dimensional position. The computer detects, from an image data, an area in which a designated target object is included. The computer extracts, from three-dimensional point cloud data, extraction point cloud data representing a three-dimensional position of an object in a target area. The computer generates target object information. A shape and an orientation of a first portion of the designated target object are defined. The orientation is defined for one of coordinate axes in the reference coordinate system. The computer generates the target object information by fitting the target object model to the extraction point cloud data under a condition that an orientation of the target object model matches an orientation defined for the first portion.

公开(公告)号：US20210383213A1

公开(公告)日：2021-12-09

申请号：US17182282

申请日：2021-02-23

申请人： KABUSHIKI KAISHA TOSHIBA

发明人： Atsushi KAWASAKI

IPC分类号： G06N3/08 ,  G06N3/04

摘要： A prediction device according to an embodiment includes one or more hardware processors. The hardware processors acquire moving object information indicating the positions of one or more moving objects including a first moving object to be predicted. The hardware processors generate cumulative map information expressing, on a map, a plurality of positions indicated by the moving object information acquired at a plurality of first time points equal to or earlier than the reference time point. The hardware processors predict a position of the first moving object at a second time point later than the reference time point based on environment map information expressing, on a map, an environment around the first moving object at the reference time point, moving object information acquired at the reference time point, and the cumulative map information.

公开(公告)号：US20190009783A1

公开(公告)日：2019-01-10

申请号：US15897657

申请日：2018-02-15

申请人： Kabushiki Kaisha Toshiba

发明人： Atsushi KAWASAKI ,  Tsuyoshi Tasaki

IPC分类号： B60W30/18

摘要： According to an embodiment, an information processing apparatus includes one or more processors configured to: acquire a dynamic state related to traveling of a moving object entering an intersection; acquire intersection information indicating a configuration of the intersection; specify a reference route along which the moving object is predicted to travel at the intersection, based on the dynamic state and the intersection information; detect a speed control point that is a position included in the specified reference route; and generate a speed model representing a temporal change in a predicted speed of the moving object so that the speed at the speed control point is locally minimized, based on the dynamic state and the intersection information.

公开(公告)号：US20220057992A1

公开(公告)日：2022-02-24

申请号：US17184661

申请日：2021-02-25

申请人： KABUSHIKI KAISHA TOSHIBA

发明人： Atsushi KAWASAKI

IPC分类号： G06F7/523 ,  G06F17/18 ,  B60W30/095 ,  B60W30/09 ,  B60W50/00

摘要： An information processing system according to an embodiment includes one or more hardware processors. The hardware processors acquire an n-dimensional vector. The hardware processors generate n coordinate arrays, where the n coordinate arrays is n pieces of n-dimensional arrays for which, with respect to each of elements of an m-th array (1≤m≤n), an element value having a same value as an index of an m-th dimensional coordinate of the elements is set. The hardware processors obtain n first probability distribution arrays including an output value of a probability density function as an element value corresponding to each of the n coordinate arrays, multiply n element values for each of elements corresponding to each of the n first probability distribution arrays, and obtain a second probability distribution array having a result of multiplication as an element value.