公开(公告)号：US11610330B2

公开(公告)日：2023-03-21

申请号：US17063909

申请日：2020-10-06

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Chuangqi Tang ,  Yuguang Li ,  Zhuo Li

IPC: G06T7/73 ,  G06T7/246

Abstract: A pose tracking method and apparatus are disclosed. The pose tracking method includes obtaining an image of a trackable target having a plurality of markers, detecting first points in the obtained image to which the markers are projected, matching the first points and second points corresponding to positions of the markers in a coordinate system set based on the trackable target based on rotation information of the trackable target, and estimating a pose of the trackable target based on matching pairs of the first points and the second points.

公开(公告)号：US11488320B2

公开(公告)日：2022-11-01

申请号：US16943048

申请日：2020-07-30

Applicant: Samsung Electronics Co., Ltd.

Inventor： Huiguang Yang ,  Jiguang Xue ,  Zhuo Li ,  Chuangqi Tang ,  Xiongzhan Linghu ,  Yuguang Li ,  Liu Yang ,  Jian Zhao ,  Manjun Yan

IPC: G06T7/73

Abstract: A pose estimation method includes obtains an event stream from an event-based vision sensor configured to capture a target object to which light-emitting devices flickering at a predetermined first frequency are attached, obtains a polarity change period of at least one pixel based on the event stream, generates an image frame sequence using at least one target pixel having a polarity change period corresponding to the first frequency, among the at least one pixel, extracts a feature sequence including feature vectors corresponding to the at least one target pixel, from the image frame sequence, and estimates a pose sequence of the target object by applying the feature sequence to a deep neural network (DNN) model.

公开(公告)号：US11430150B2

公开(公告)日：2022-08-30

申请号：US17123540

申请日：2020-12-16

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Zhuo Li ,  Huiguang Yang ,  Yuguang Li ,  Liu Yang

IPC: G06T7/73 ,  G06T7/77

Abstract: A method and apparatus for processing sparse points. The method includes determining spatial hierarchical point data based on a key point set and a local point set of a sparse point set, determining relationship feature data by encoding a spatial hierarchical relationship between points of the spatial hierarchical point data, generating a global feature and a local feature of the sparse point set through a conversion operation associated with the relationship feature data, and generating a processing result for the sparse point set based on the global feature and the local feature.