Vetrivel et al., 2015 - Google Patents
Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne imagesVetrivel et al., 2015
View PDF- Document ID
- 12260444023694647070
- Author
- Vetrivel A
- Gerke M
- Kerle N
- Vosselman G
- Publication year
- Publication venue
- ISPRS journal of photogrammetry and remote sensing
External Links
Snippet
Point clouds generated from airborne oblique images have become a suitable source for detailed building damage assessment after a disaster event, since they provide the essential geometric and radiometric features of both roof and façades of the building. However, they …
- 238000000034 method 0 abstract description 62
Classifications
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- 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
- G06K9/32—Aligning or centering of the image pick-up or image-field
- G06K9/3233—Determination of region of interest
-
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
-
- 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
- G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
-
- 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
- G06K9/34—Segmentation of touching or overlapping patterns in the image field
- G06K9/342—Cutting or merging image elements, e.g. region growing, watershed, clustering-based techniques
-
- 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
- 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
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
-
- 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
- G06T2207/30108—Industrial image inspection
-
- 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
- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
-
- 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
- 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
- G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Vetrivel et al. | Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images | |
Zakeri et al. | Image based techniques for crack detection, classification and quantification in asphalt pavement: a review | |
US10346687B2 (en) | Condition detection using image processing | |
Zhang et al. | Change detection between multimodal remote sensing data using Siamese CNN | |
Serna et al. | Detection, segmentation and classification of 3D urban objects using mathematical morphology and supervised learning | |
Gerke et al. | Automatic structural seismic damage assessment with airborne oblique Pictometry© imagery | |
CA2994508C (en) | Vegetation management for power line corridor monitoring using computer vision | |
Zhou et al. | Automated residential building detection from airborne LiDAR data with deep neural networks | |
Teodoro et al. | Comparison of performance of object-based image analysis techniques available in open source software (Spring and Orfeo Toolbox/Monteverdi) considering very high spatial resolution data | |
Xia et al. | Extraction of residential building instances in suburban areas from mobile LiDAR data | |
Gevaert et al. | Classification of informal settlements through the integration of 2D and 3D features extracted from UAV data | |
Li | Optimising detection of road furniture (pole-like objects) in mobile laser scanning data | |
Xiao et al. | 3D urban object change detection from aerial and terrestrial point clouds: A review | |
Khodaverdizahraee et al. | Segment-by-segment comparison technique for earthquake-induced building damage map generation using satellite imagery | |
Farmakis et al. | Supervoxel-based multi-scale point cloud segmentation using FNEA for object-oriented rock slope classification using TLS | |
Zahs et al. | Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data | |
Chandra et al. | Building detection methods from remotely sensed images | |
Sharma et al. | Building footprint extraction from aerial photogrammetric point cloud data using its geometric features | |
Lucks et al. | Superpixel-wise Assessment of Building Damage from Aerial Images. | |
Feng et al. | Automated extraction of building instances from dual-channel airborne LiDAR point clouds | |
Yu et al. | Bidirectionally greedy framework for unsupervised 3D building extraction from airborne-based 3D meshes | |
Khodaverdi et al. | Combination of post-earthquake LiDAR data and satellite imagery for buildings damage detection | |
Zhan et al. | Objects classification from laser scanning data based on multi-class support vector machine | |
Zhang | Photogrammetric point clouds: quality assessment, filtering, and change detection | |
Wang | Understanding high resolution aerial imagery using computer vision techniques |