[go: up one dir, main page]

Nurunnabi et al., 2023 - Google Patents

Detection and Segmentation of Pole-like Objects in Mobile Laser Scanning Point Clouds

Nurunnabi et al., 2023

View PDF
Document ID
15459647736541473788
Author
Nurunnabi A
Sadahiro Y
Teferle F
Laefer D
Li J
Publication year
Publication venue
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

External Links

Snippet

Pole-like object (PLO) detection and segmentation are important in many applications, such as 3D city modelling, urban planning, road assets monitoring, intelligent transportation, road safety, and forest monitoring. Arguably, vehicle-based mobile laser scanning (MLS) is the …
Continue reading at isprs-archives.copernicus.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20Image acquisition
    • G06K9/32Aligning or centering of the image pick-up or image-field
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30181Earth observation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00362Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
    • G06K9/00369Recognition of whole body, e.g. static pedestrian or occupant recognition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05Geographic models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G06F17/30799Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content

Similar Documents

Publication Publication Date Title
Zai et al. 3-D road boundary extraction from mobile laser scanning data via supervoxels and graph cuts
Holgado‐Barco et al. Automatic inventory of road cross‐sections from mobile laser scanning system
Cheng et al. Extraction and classification of road markings using mobile laser scanning point clouds
Yu et al. Automated extraction of urban road facilities using mobile laser scanning data
Yu et al. Learning hierarchical features for automated extraction of road markings from 3-D mobile LiDAR point clouds
Yu et al. Semiautomated extraction of street light poles from mobile LiDAR point-clouds
EP4128033A1 (en) Feature extraction from mobile lidar and imagery data
Ye et al. Robust lane extraction from MLS point clouds towards HD maps especially in curve road
Soilán et al. Automatic extraction of road features in urban environments using dense ALS data
Xu et al. Unsupervised segmentation of point clouds from buildings using hierarchical clustering based on gestalt principles
CN105260737B (en) A kind of laser scanning data physical plane automatization extracting method of fusion Analysis On Multi-scale Features
Sohn et al. Building extraction using Lidar DEMs and Ikonos images
US6453056B2 (en) Method and apparatus for generating a database of road sign images and positions
Chen et al. Next generation map making: Geo-referenced ground-level LIDAR point clouds for automatic retro-reflective road feature extraction
Teo et al. Pole-like road object detection from mobile lidar system using a coarse-to-fine approach
Yao et al. Extraction and motion estimation of vehicles in single-pass airborne LiDAR data towards urban traffic analysis
Lin et al. CNN-based classification for point cloud object with bearing angle image
Yu et al. Bag of contextual-visual words for road scene object detection from mobile laser scanning data
Zhang et al. GC-Net: Gridding and clustering for traffic object detection with roadside LiDAR
Pan et al. Automatic road markings extraction, classification and vectorization from mobile laser scanning data
Shokri et al. Utility poles extraction from mobile lidar data in urban area based on density information
Sohn et al. A data-driven method for modeling 3D building objects using a binary space partitioning tree
Börcs et al. A model-based approach for fast vehicle detection in continuously streamed urban LIDAR point clouds
Bretar Feature extraction from LiDAR data in urban areas
Nurunnabi et al. Detection and Segmentation of Pole-like Objects in Mobile Laser Scanning Point Clouds