公开(公告)号：US20190034509A1

公开(公告)日：2019-01-31

申请号：US16049709

申请日：2018-07-30

Applicant: Hefei University of Technology

Inventor： Shuai DING ,  Shanlin YANG ,  Qiang FU ,  Lin ZHANG

IPC: G06F17/30 ,  H04L29/08

Abstract: The present invention provides a method and system for synchronously storing multi-modal information of portable endoscope. The method includes: S1: when a mobile terminal acquires data collected by a portable endoscope and updates local data with the acquired data, acquiring update record of the local data of the mobile terminal; and, S2: when the mobile terminal is synchronized with a cloud, synchronizing data in the mobile terminal with data in the cloud by using the update record as information to be synchronized. By creating a table to be synchronized to store change information and location information of files and selectively performing synchronization from the mobile terminal to the cloud or from the cloud to the mobile terminal according to whether or not the table to be synchronized is null during synchronization, unnecessary synchronization operations, storage burden of the mobile terminal and synchronization time and traffic are all reduced.

公开(公告)号：US20240005532A1

公开(公告)日：2024-01-04

申请号：US18346331

申请日：2023-07-03

Applicant: Hefei University of Technology

Inventor： Xiaojian LI ,  Ling LI ,  Shanlin YANG ,  Youtong TANTAI ,  Jin FANG ,  Jieyu ZHENG ,  Shuai DING ,  Lin ZHANG ,  Yanwei QU ,  Hua TANG ,  Liangkuan BI

IPC: G06T7/246 ,  G06T7/73 ,  G06T7/50 ,  G06T7/60 ,  G06T3/00 ,  G06V10/46

CPC classification number: G06T7/248 ,  G06T7/74 ,  G06T7/50 ,  G06T7/60 ,  G06T3/0006 ,  G06V10/462 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/10068 ,  G06T2207/30004

Abstract: Dynamic tracking methods for an in-vivo three-dimensional key point and an in-vivo three-dimensional curve can include mapping a first local region to a first local point cloud and mapping a second local region to a second local point cloud according to a mapping relation between an endoscopic image and the point clouds; determining a first three-dimensional key point of a first two-dimensional key point on the first local point cloud, and acquiring a second three-dimensional key point on the second local point cloud through a coordinate transformation; and mapping the second three-dimensional key point back to the second local region, so as to acquire a second two-dimensional key point from a next image; and acquiring two-dimensional coordinates of a tracked key point by minimizing a preset optimization function in combination with an initial two-dimensional key point, and finally acquiring corresponding three-dimensional coordinates.