公开(公告)号：US11222465B2

公开(公告)日：2022-01-11

申请号：US17043580

申请日：2020-02-27

Applicant: SOUTHEAST UNIVERSITY

Inventor： Junyan Yang ,  Jun Cao ,  Qingyao Zhang ,  Beixiang Shi ,  Yi Shi

IPC: G06T17/05 ,  G06T7/40 ,  G06T7/60 ,  G06T19/20 ,  G06T17/00

Abstract: The present invention discloses an embedded urban design scene emulation method and system. The method includes the following steps: constructing a status quo urban three-dimensional model scene according to collected oblique photography data; loading a three-dimensional model of urban design to a scene, and extracting geometric attributes for generation of buildings; unifying a space coordinate system of models and scenes, and automatically determining a space matching degree by taking buildings as a basic unit, and marking matched buildings with Y and mismatched buildings with N for distinction; for a region with the buildings marked with N, performing a local flattening operation in a three-dimensional model scene of oblique photography to flatten stereo data; for a region with the buildings marked with Y, performing real-time space editing in the three-dimensional model of urban design to hide the marked buildings; and opening two sets of processed space data to implement mosaic display. The present invention can conveniently embed a three-dimensional model of urban design into a status quo three-dimensional model of oblique photography for scene emulation, and provides technical and method supports for digital presentation and management of urban design achievements.

公开(公告)号：US10467199B2

公开(公告)日：2019-11-05

申请号：US15529196

申请日：2016-05-09

Applicant: SOUTHEAST UNIVERSITY

Inventor： Junyan Yang ,  Weiting Xiong ,  Yi Shi

IPC: G06F16/20 ,  H04W4/02 ,  G06F16/29 ,  H04W4/029

Abstract: A definition method for urban dynamic spatial structure circle comprising steps of: collecting the location data of mobile phone users for cleaning and handling to obtain a matched location data of mobile phone user; incorporating the matched location data of mobile phone user at various moments into a daily location data of mobile phone according to the date with a base station being the unit; locating spatially each base station with different users in a whole city through Tyson polygon processing method addressing the incorporated base station information; distributing the data of user number in each polygon into each land plot contained therein; obtaining mobile phone user distribution multi-circle numerical law on each moment and workday and finding the critical point of value, delineating the urban dynamic spatial structure circle distribution map after combining the circles in the same plot area.

公开(公告)号：US12048549B1

公开(公告)日：2024-07-30

申请号：US18565501

申请日：2023-04-04

Applicant: SOUTHEAST UNIVERSITY

Inventor： Zhe Li ,  Liya Wang ,  Xiao Han ,  Jie Li ,  Qixin Zhang ,  Mingjing Dong ,  Mingchen Xu ,  Shuang Wu ,  Yi Shi ,  Haini Chen ,  Qiaochu Wang

IPC: G06V10/00 ,  A61B5/0205 ,  A61B5/0533 ,  A61B5/352 ,  A61B5/378 ,  A61B5/397 ,  G06N20/00 ,  G06V10/26 ,  G06V10/764 ,  G06V20/00 ,  G06Q50/26

CPC classification number: A61B5/378 ,  A61B5/0205 ,  A61B5/0533 ,  A61B5/352 ,  A61B5/397 ,  G06N20/00 ,  G06V10/26 ,  G06V10/764 ,  G06V20/39 ,  A61B2503/12 ,  G06Q50/26

Abstract: A street greening quality detection method based on physiological activation recognition is provided. The street greening quality detection method includes establishing a greening quality factor index system, and obtaining and uniformly processing street greening images; collecting raw data, and performing reclassification and differential wave processing on the raw data to obtain valid physiological data that can be used for activation feature recognition of greening quality factors; calculating physiological activation feature parameters, training the physiological activation feature parameters by transfer learning fusion to determine importance of physiological activation features, and recognizing weighted average greening activation indexes of the greening quality factors; analyzing weighted average greening activation index data of the greening quality factors to form a street greening quality detection model; and inputting annotated street samples to be analyzed into the street greening quality detection model to obtain annotated results of street greening quality grading detection target data.