Shi et al., 2022 - Google Patents
Lane-level road network construction based on street-view imagesShi et al., 2022
View PDF- Document ID
- 517241211812723924
- Author
- Shi J
- Li G
- Zhou L
- Lü G
- Publication year
- Publication venue
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
External Links
Snippet
With the advancement of autonomous driving technologies, road network data have attracted a lot of attention as a virtual source of information. Traditional node–arc road networks are no longer able to match the demands of high-precision location awareness …
- 238000010276 construction 0 title abstract description 6
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/20—Image acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/60—Editing figures and text; Combining figures or text
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30241—Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T15/00—3D [Three Dimensional] image rendering
- G06T15/10—Geometric effects
- G06T15/20—Perspective computation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP7485749B2 (en) | Video-based localization and mapping method and system - Patents.com | |
US10670416B2 (en) | Traffic sign feature creation for high definition maps used for navigating autonomous vehicles | |
Qin et al. | 3D change detection–approaches and applications | |
Mattyus et al. | Enhancing road maps by parsing aerial images around the world | |
US11590989B2 (en) | Training data generation for dynamic objects using high definition map data | |
Zhao et al. | Lidar mapping optimization based on lightweight semantic segmentation | |
Zhou et al. | Developing and testing robust autonomy: The university of sydney campus data set | |
Ma et al. | Boundarynet: extraction and completion of road boundaries with deep learning using mobile laser scanning point clouds and satellite imagery | |
CN115294293B (en) | Method for automatically compiling high-precision map road reference line based on low-altitude aerial photography result | |
CN115690138A (en) | Road boundary extraction and vectorization method fusing vehicle-mounted image and point cloud | |
CN111626971B (en) | Smart city CIM real-time imaging method with image semantic perception | |
Huang et al. | Overview of LiDAR point cloud target detection methods based on deep learning | |
Shi et al. | Lane-level road network construction based on street-view images | |
Song et al. | A CPU-GPU hybrid system of environment perception and 3D terrain reconstruction for unmanned ground vehicle | |
Liu et al. | 3D point cloud segmentation using GIS | |
CN114820931B (en) | Virtual reality-based CIM (common information model) visual real-time imaging method for smart city | |
Zhu | A pipeline of 3D scene reconstruction from point clouds | |
Ozcanli et al. | Geo-localization using volumetric representations of overhead imagery | |
CN111784822A (en) | Smart city CIM real-time imaging method with image semantic perception | |
Liu et al. | UEMM-Air: A Synthetic Multi-modal Dataset for Unmanned Aerial Vehicle Object Detection | |
Mao et al. | Large Area Building Detection from Airborne Lidar Data using OSM Trained Superpixel Classification | |
Dong | A Review of Traffic Scene Reconstruction Based on Images and Point Clouds | |
Kwag et al. | A Review on End-to-End High-Definition Map Generation | |
Steinhage et al. | Reconstruction by components for automated updating of 3D city models | |
Du et al. | Road extraction method of vehicle trajectory data based on geo-referenced videos |