Chen et al., 2023 - Google Patents
A Framework of Reconstructing Piping Systems on Classimbalanced 3D Point Cloud Data from Construction SitesChen et al., 2023
- Document ID
- 5144215388318269082
- Author
- Chen Y
- Kim S
- Ahn Y
- Cho Y
- Publication year
- Publication venue
- ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction
External Links
Snippet
In construction environments, modifications to the dimensions, positioning, and trajectory of plumbing infrastructure within edifices are frequently necessitated by on-site conditions and pragmatic installation procedures. Recent advancements in Scan-to-BIM technology have …
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
- G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
-
- 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
- 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
- G06T2207/30148—Semiconductor; IC; Wafer
-
- 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
- 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
-
- 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
- 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
- G06K9/00664—Recognising scenes such as could be captured by a camera operated by a pedestrian or robot, including objects at substantially different ranges from the camera
- G06K9/00684—Categorising the entire scene, e.g. birthday party or wedding scene
- G06K9/00697—Outdoor scenes
- G06K9/00704—Urban 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
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- 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
- 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
- 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
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Cha et al. | Deep learning-based structural health monitoring | |
Kim et al. | Automatic pipe and elbow recognition from three-dimensional point cloud model of industrial plant piping system using convolutional neural network-based primitive classification | |
Kim et al. | Deep-learning-based retrieval of piping component catalogs for plant 3D CAD model reconstruction | |
CN111527467A (en) | Method and apparatus for automatically defining computer-aided design files using machine learning, image analysis, and/or computer vision | |
Zheng et al. | Identification and characterization of particle shapes from images of sand assemblies using pattern recognition | |
Czerniawski et al. | Automated removal of planar clutter from 3D point clouds for improving industrial object recognition | |
Khankeshizadeh et al. | A novel weighted ensemble transferred U-Net based model (WETUM) for postearthquake building damage assessment from UAV data: A comparison of deep learning-and machine learning-based approaches | |
CN113807301A (en) | Automatic extraction method and automatic extraction system for newly-added construction land | |
Reghukumar et al. | Vision based segmentation and classification of cracks using deep neural networks | |
Zhang et al. | Concrete crack quantification using voxel-based reconstruction and Bayesian data fusion | |
Bulatov et al. | Classification of airborne 3D point clouds regarding separation of vegetation in complex environments | |
Rani et al. | Advancements in point cloud-based 3D defect classification and segmentation for industrial systems: A comprehensive survey | |
Zhao et al. | A review of point cloud segmentation of architectural cultural heritage | |
Jiang et al. | A method of concrete damage detection and localization based on weakly supervised learning | |
Chen et al. | A Framework of Reconstructing Piping Systems on Classimbalanced 3D Point Cloud Data from Construction Sites | |
Elghaish et al. | Multi-layers deep learning model with feature selection for automated detection and classification of highway pavement cracks | |
Sun et al. | Automated segmentation of LiDAR point clouds for building rooftop extraction | |
CN118365969A (en) | Intelligent robot-based all-condition urban underground pipe culvert detection method and system | |
Elhariri et al. | Performance analysis of using feature fusion for crack detection in images of historical buildings | |
Zhu et al. | BY-SLAM: Dynamic Visual SLAM System Based on BEBLID and Semantic Information Extraction | |
Widyaningrum et al. | Tailored features for semantic segmentation with a DGCNN using free training samples of a colored airborne point cloud | |
Satari et al. | Extraction of linear structures from digital terrain models using deep learning | |
Daghigh | Efficient automatic extraction of discontinuities from rock mass 3D point cloud data using unsupervised machine learning and RANSAC | |
Zhang et al. | Multi-Data UAV Images for Large Scale Reconstruction of Buildings | |
Zhang | Surface defect detection, segmentation and quantification for concrete bridge assessment using deep learning and 3D reconstruction |