公开(公告)号：US20230334819A1

公开(公告)日：2023-10-19

申请号：US18213073

申请日：2023-06-22

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Dongning HAO ,  Guotao SHEN ,  Xiaoli ZHU ,  Qiang HUANG ,  Longhai WU ,  Jie CHEN

IPC: G06V10/60 ,  G06V10/75 ,  G06T7/70

CPC classification number: G06V10/60 ,  G06V10/757 ,  G06T7/70

Abstract: An illuminant estimation method, including acquiring two image frames, wherein a distance between the two image frames is greater than a predetermined distance; detecting shadows included in the two image frames, extracting pixel feature points corresponding to the shadows, determining point cloud information about the shadows, and distinguishing a point cloud of each shadow based on the point cloud information about the shadows; acquiring point cloud information about multiple objects, and distinguishing a point cloud of each object based on the point cloud information corresponding to the multiple objects; matching the point cloud of the each shadow and the point cloud of the each object in order to determine corresponding shadows associated with the multiple objects; and determining a position of an illuminant according to a positional relation between the multiple objects and the corresponding shadows.

公开(公告)号：US20230281829A1

公开(公告)日：2023-09-07

申请号：US18168209

申请日：2023-02-13

Applicant: Samsung Electronics Co., Ltd.

Inventor： Xin JIN ,  Guotao SHEN ,  Youxin CHEN ,  Longhai WU ,  Jie CHEN ,  Jayoon KOO

IPC: G06T7/20 ,  G06T3/00 ,  G06T3/40

CPC classification number: G06T7/20 ,  G06T3/0093 ,  G06T3/40 ,  G06T2207/20016 ,  G06T2207/20084

Abstract: A bidirectional optical flow estimation method and apparatus are provided. The method includes acquiring a target image pair of which optical flow is to be estimated, and constructing an image pyramid for each target image in the target image pair respectively, and performing bidirectional optical flow estimation using a pre-trained optical flow estimation model based on the image pyramid, to obtain bidirectional optical flow between the target images. An optical flow estimation module in the optical flow estimation model is recursively called to perform the bidirectional optical flow estimation sequentially based on images of respective layers in the image pyramid according to a preset order, forward warping towards middle processing is performed on an image of a corresponding layer of the image pyramid before each call of the optical flow estimation module, and an image of an intermediate frame obtained by the forward warping towards middle processing is inputted into the optical flow estimation module. With the disclosure, the efficiency and generalization of bidirectional optical flow estimation can be improved, and model training and optical flow estimation overheads can be reduced.