Search results for " Point cloud"

showing 4 items of 14 documents

Region-based segmentation on depth images from a 3D reference surface for tree species recognition.

2013

International audience; The aim of the work presented in this paper is to develop a method for the automatic identification of tree species using Terrestrial Light Detection and Ranging (T-LiDAR) data. The approach that we propose analyses depth images built from 3D point clouds corresponding to a 30 cm segment of the tree trunk in order to extract characteristic shape features used for classifying the different tree species using the Random Forest classifier. We will present the method used to transform the 3D point cloud to a depth image and the region based segmentation method used to segment the depth images before shape features are computed on the segmented images. Our approach has be…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingFeature extractionPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Minimum spanning tree-based segmentation[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[STAT.AP]Statistics [stat]/Applications [stat.AP]Contextual image classificationbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentation15. Life on landdepth image segmentationRandom forestdepth images from 3D point cloudsIEEE[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]020201 artificial intelligence & image processingsingle tree species recognitionArtificial intelligenceRange segmentationbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingForest inventory
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SCAN-TO-BIM FOR THE MANAGEMENT OF HERITAGE BUILDINGS: THE CASE STUDY OF THE CASTLE OF MAREDOLCE (PALERMO, ITALY)

2020

Abstract. Conservation and preservation of heritage buildings require the knowledge and sharing of a great deal of data and information about buildings. Such information comes from the different disciplines involved in the restoration and maintenance processes. The integration and use of all this information in a single working environment is a key factor for the success of historical building conservation and management projects. Heritage (or Historic) Building Information Modelling (HBIM) is nowadays the most appropriate tool to collect and manage all data related to Architectural Heritage. The HBIM process requires an in-depth knowledge of the historical building that can be achieved usi…

lcsh:Applied optics. Photonics3D modelling HBIM Laser scanner Point cloud Scan-to-BIMEngineeringArchitectural engineeringProcess (engineering)Settore ICAR/10 - Architettura Tecnica02 engineering and technologylcsh:Technology01 natural sciencesArchitectural heritage0202 electrical engineering electronic engineering information engineeringParametric modellingParametric statisticslcsh:Tbusiness.industry010401 analytical chemistrylcsh:TA1501-18200104 chemical sciencesBuilding information modelingWork (electrical)lcsh:TA1-2040Settore ICAR/17 - Disegno020201 artificial intelligence & image processinglcsh:Engineering (General). Civil engineering (General)businessSettore ICAR/06 - Topografia E CartografiaWorking environmentThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Tree species recognition in species rich area using UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud

2017

Abstract. Recognition of tree species and geospatial information of tree species composition is essential for forest management. In this study we test tree species recognition using hyperspectral imagery from VNIR and SWIR camera sensors in combination with 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum forest with a high number of tree species was used as a test area. The imagery was acquired from the test area using UAV-borne cameras. Hyperspectral imagery was calibrated for providing a radiometrically corrected reflectance mosaic, which was tested along with the original uncalibrated imagery. Alternative estimators were tested for predicting tree…

lcsh:Applied optics. Photonicshyperspectral imaging0211 other engineering and technologiesPoint cloud02 engineering and technologyUAVslcsh:TechnologyImage sensor021101 geological & geomatics engineeringRemote sensing040101 forestryPixellcsh:Ttree species recognitionlcsh:TA1501-1820Hyperspectral imaging04 agricultural and veterinary sciencesOtaNanoVNIRTree (data structure)GeographyPhotogrammetryphotogrammetric point cloudlcsh:TA1-2040stereo-photogrammetry0401 agriculture forestry and fisheriesRGB color modellcsh:Engineering (General). Civil engineering (General)
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Editorial for the Special Issue “Frontiers in Spectral Imaging and 3D Technologies for Geospatial Solutions”

2019

This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was used in object analysis.

medicine.medical_specialtyGeospatial analysisComputer sciencehyperspectral imagingSciencecomputer.software_genrehyperspectral imaging; point cloud; sensor integration; data fusion; machine learning; deep learning; classification; estimation; semantic segmentation; object detection; point cloud filteringmedicine3D-mallinnussensor integrationpoint cloud filteringdata fusionestimationbusiness.industryDeep learningspektrikuvausQHyperspectral imagingdeep learningobject detectionSensor fusionObject (computer science)Data scienceObject detectionsemantic segmentationSpectral imagingVariety (cybernetics)classificationpoint cloud filteringsegmentointikoneoppiminenmachine learningclassificationGeneral Earth and Planetary SciencesArtificial intelligencekaukokartoitusbusinesscomputerpoint cloudRemote Sensing
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