WHICH 3D DATA REPRESENTATION DOES THE CROWD LIKE BEST? CROWD-BASED ACTIVE LEARNING FOR COUPLED SEMANTIC SEGMENTATION OF POINT CLOUDS AND TEXTURED MESHES

Kölle, M.; Laupheimer, D.; Walter, V.; Haala, N.; Soergel, U.

doi:https://doi.org/10.5194/isprs-annals-V-2-2021-93-2021

FROM MULTIPLE POLYGONS TO SINGLE GEOMETRY: OPTIMIZATION OF POLYGON INTEGRATION FOR CROWDSOURCED DATA

D. Collmar, V. Walter, M. Kölle, and U. Sörgel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 159–166, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-159-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-159-2023, 2023

VEHICLE OCCLUSION REMOVAL FROM SINGLE AERIAL IMAGES USING GENERATIVE ADVERSARIAL NETWORKS

M. Xiang, S. Azimi, R. Bahmanyar, U. Sörgel, and P. Reinartz

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 629–634, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-629-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-629-2023, 2023

DEVELOPMENT OF A WEB PLATFORM TO VISUALIZE PS-INSAR DATA IN A BUILDING INFORMATION MANAGEMENT SYSTEM

P. J. Schneider, C.-H. Yang, Y. Li, M. Koppe, U. Soergel, K. Pakzad, and T. Rudolf

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 869–873, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-869-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-869-2023, 2023

LEARNING ON THE EDGE: BENCHMARKING ACTIVE LEARNING FOR THE SEMANTIC SEGMENTATION OF ALS POINT CLOUDS

M. Kölle, V. Walter, S. Schmohl, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 945–952, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-945-2023,https://doi.org/10.5194/isprs-annals-X-1-W1-2023-945-2023, 2023

GEOMETRIC PROCESSING OF VERY HIGH-RESOLUTION SATELLITE IMAGERY: QUALITY ASSESSMENT FOR 3D MAPPING NEEDS

E. M. Farella, F. Remondino, C. Cahalane, R. Qin, A. M. Loghin, M. Di Tullio, N. Haala, and J. Mills

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 47–54, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-47-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-47-2023, 2023

EVALUATION OF CONSUMER-GRADE AND SURVEY-GRADE UAV-LIDAR

G. Mandlburger, M. Kölle, F. Pöppl, and M. Cramer

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W3-2023, 99–106, https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-99-2023,https://doi.org/10.5194/isprs-archives-XLVIII-1-W3-2023-99-2023, 2023

GLOBALLY OPTIMAL POINT CLOUD REGISTRATION FOR ROBUST MOBILE MAPPING

D. Skuddis and N. Haala

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 273–281, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-273-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-273-2022, 2022

A TWO-STAGE APPROACH FOR RARE CLASS SEGMENTATION IN LARGE-SCALE URBAN POINT CLOUDS

X. Zhang, R. Xue, and U. Soergel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 329–334, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-329-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-329-2022, 2022

EVALUATION OF THE QUALITY OF REAL-TIME MAPPING WITH CRANE CAMERAS AND VISUAL SLAM ALGORITHMS

L. Joachim, W. Zhang, N. Haala, and U. Soergel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 545–552, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-545-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-545-2022, 2022

THE EUROSDR TIME BENCHMARK FOR HISTORICAL AERIAL IMAGES

E. M. Farella, L. Morelli, F. Remondino, J. P. Mills, N. Haala, and J. Crompvoets

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1175–1182, https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022,https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022, 2022

URBAN CLASSIFICATION BASED ON TOP-VIEW POINT CLOUD AND SAR IMAGE FUSION WITH SWIN TRANSFORMER

R. Xue, X. Zhang, and U. Soergel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 559–564, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-559-2022,https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-559-2022, 2022

A GAMIFICATION APPROACH FOR THE IMPROVEMENT OF PAID CROWD-BASED LABELLING OF GEOSPATIAL DATA

V. Walter, M. Kölle, and D. Collmar

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2022, 113–120, https://doi.org/10.5194/isprs-annals-V-4-2022-113-2022,https://doi.org/10.5194/isprs-annals-V-4-2022-113-2022, 2022

TOWARDS ROBUST INDOOR VISUAL SLAM AND DENSE RECONSTRUCTION FOR MOBILE ROBOTS

W. Zhang, S. Wang, and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2022, 211–219, https://doi.org/10.5194/isprs-annals-V-1-2022-211-2022,https://doi.org/10.5194/isprs-annals-V-1-2022-211-2022, 2022

LEARNING FROM THE PAST: CROWD-DRIVEN ACTIVE TRANSFER LEARNING FOR SEMANTIC SEGMENTATION OF MULTI-TEMPORAL 3D POINT CLOUDS

M. Kölle, V. Walter, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 259–266, https://doi.org/10.5194/isprs-annals-V-2-2022-259-2022,https://doi.org/10.5194/isprs-annals-V-2-2022-259-2022, 2022

MULTI-MODAL SEMANTIC MESH SEGMENTATION IN URBAN SCENES

D. Laupheimer and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 267–274, https://doi.org/10.5194/isprs-annals-V-2-2022-267-2022,https://doi.org/10.5194/isprs-annals-V-2-2022-267-2022, 2022

MATCHING PERSISTENT SCATTERER CLUSTERS TO BUILDING ELEMENTS IN MESH REPRESENTATION

P. J. Schneider and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 123–130, https://doi.org/10.5194/isprs-annals-V-3-2022-123-2022,https://doi.org/10.5194/isprs-annals-V-3-2022-123-2022, 2022

SEGMENTATION OF BUILDINGS BASED ON HIGH RESOLUTION PERSISTENT SCATTERER POINT CLOUDS

P. J. Schneider and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 65–71, https://doi.org/10.5194/isprs-annals-V-3-2021-65-2021,https://doi.org/10.5194/isprs-annals-V-3-2021-65-2021, 2021

A TWO-LEVEL APPROACH FOR THE CROWD-BASED COLLECTION OF VEHICLES FROM 3D POINT CLOUDS

V. Walter, M. Kölle, D. Collmar, and Y. Zhang

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2021, 97–104, https://doi.org/10.5194/isprs-annals-V-4-2021-97-2021,https://doi.org/10.5194/isprs-annals-V-4-2021-97-2021, 2021

THREE-DIMENSIONAL PATH PLANNING OF UAVS IMAGING FOR COMPLETE PHOTOGRAMMETRIC RECONSTRUCTION

S. Zhang, C. Liu, and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-1-2020, 325–331, https://doi.org/10.5194/isprs-annals-V-1-2020-325-2020,https://doi.org/10.5194/isprs-annals-V-1-2020-325-2020, 2020

HYBRID ACQUISITION OF HIGH QUALITY TRAINING DATA FOR SEMANTIC SEGMENTATION OF 3D POINT CLOUDS USING CROWD-BASED ACTIVE LEARNING

M. Kölle, V. Walter, S. Schmohl, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 501–508, https://doi.org/10.5194/isprs-annals-V-2-2020-501-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-501-2020, 2020

ON THE ASSOCIATION OF LIDAR POINT CLOUDS AND TEXTURED MESHES FOR MULTI-MODAL SEMANTIC SEGMENTATION

D. Laupheimer, M. H. Shams Eddin, and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 509–516, https://doi.org/10.5194/isprs-annals-V-2-2020-509-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-509-2020, 2020

HYBRID GEOREFERENCING, ENHANCEMENT AND CLASSIFICATION OF ULTRA-HIGH RESOLUTION UAV LIDAR AND IMAGE POINT CLOUDS FOR MONITORING APPLICATIONS

N. Haala, M. Kölle, M. Cramer, D. Laupheimer, G. Mandlburger, and P. Glira

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 727–734, https://doi.org/10.5194/isprs-annals-V-2-2020-727-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-727-2020, 2020

IDENTIFICATION OF PEACH TREE TRUNKS FROM LASER SCANNING DATA OBTAINED WITH SMALL UNMANNED AERIAL SYSTEM

E. Hadas, M. Kölle, M. Karpina, and A. Borkowski

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 735–740, https://doi.org/10.5194/isprs-annals-V-2-2020-735-2020,https://doi.org/10.5194/isprs-annals-V-2-2020-735-2020, 2020

EXTRACTING AND EVALUATING CLUSTERS IN DINSAR DEFORMATION DATA ON SINGLE BUILDINGS

P. J. Schneider, R. Khamis, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2020, 157–163, https://doi.org/10.5194/isprs-annals-V-3-2020-157-2020,https://doi.org/10.5194/isprs-annals-V-3-2020-157-2020, 2020

EVALUATION AND OPTIMISATION OF CROWD-BASED COLLECTION OF TREES FROM 3D POINT CLOUDS

V. Walter, M. Kölle, and Y. Yin

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-4-2020, 49–56, https://doi.org/10.5194/isprs-annals-V-4-2020-49-2020,https://doi.org/10.5194/isprs-annals-V-4-2020-49-2020, 2020

SINGLE-IMAGE DEHAZING ON AERIAL IMAGERY USING CONVOLUTIONAL NEURAL NETWORKS

M. Madadikhaljan, R. Bahmanyar, S. M. Azimi, P. Reinartz, and U. Sörgel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W18, 687–692, https://doi.org/10.5194/isprs-archives-XLII-4-W18-687-2019,https://doi.org/10.5194/isprs-archives-XLII-4-W18-687-2019, 2019

SEMANTIC URBAN MESH ENHANCEMENT UTILIZING A HYBRID MODEL

P. Tutzauer, D. Laupheimer, and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W7, 175–182, https://doi.org/10.5194/isprs-annals-IV-2-W7-175-2019,https://doi.org/10.5194/isprs-annals-IV-2-W7-175-2019, 2019

WORKABLE MONITORING SYSTEM BASED ON SPACEBORNE SAR IMAGES FOR MINING AREAS - STINGS DEVELOPMENT PROJECT

C. H. Yang, A. Müterthies, and U. Soergel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1951–1957, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1951-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1951-2019, 2019

EVALUATION OF A PSI-BASED CHANGE DETECTION REGARDING SIMULATION, COMPARISON, AND APPLICATION

C. H. Yang and U. Soergel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1959–1965, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1959-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1959-2019, 2019

SUBMANIFOLD SPARSE CONVOLUTIONAL NETWORKS FOR SEMANTIC SEGMENTATION OF LARGE-SCALE ALS POINT CLOUDS

S. Schmohl and U. Sörgel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 77–84, https://doi.org/10.5194/isprs-annals-IV-2-W5-77-2019,https://doi.org/10.5194/isprs-annals-IV-2-W5-77-2019, 2019

ULTRA-HIGH PRECISION UAV-BASED LIDAR AND DENSE IMAGE MATCHING

M. Cramer, N. Haala, D. Laupheimer, G. Mandlburger, and P. Havel

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 115–120, https://doi.org/10.5194/isprs-archives-XLII-1-115-2018,https://doi.org/10.5194/isprs-archives-XLII-1-115-2018, 2018

INDOOR MESH CLASSIFICATION FOR BIM

L. S. Runceanu and N. Haala

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 535–539, https://doi.org/10.5194/isprs-archives-XLII-4-535-2018,https://doi.org/10.5194/isprs-archives-XLII-4-535-2018, 2018

INTEGRATION OF MULTIPLE COLLECTED POLYGONS WITH A RASTER-BASED APPROACH

V. Walter

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 679–685, https://doi.org/10.5194/isprs-archives-XLII-4-679-2018,https://doi.org/10.5194/isprs-archives-XLII-4-679-2018, 2018

ROBUST AND ACCURATE IMAGE-BASED GEOREFERENCING EXPLOITING RELATIVE ORIENTATION CONSTRAINTS

S. Cavegn, S. Blaser, S. Nebiker, and N. Haala

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 57–64, https://doi.org/10.5194/isprs-annals-IV-2-57-2018,https://doi.org/10.5194/isprs-annals-IV-2-57-2018, 2018

NEURAL NETWORKS FOR THE CLASSIFICATION OF BUILDING USE FROM STREET-VIEW IMAGERY

D. Laupheimer, P. Tutzauer, N. Haala, and M. Spicker

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 177–184, https://doi.org/10.5194/isprs-annals-IV-2-177-2018,https://doi.org/10.5194/isprs-annals-IV-2-177-2018, 2018

ADAPTIVE 4D PSI-BASED CHANGE DETECTION

Chia-Hsiang Yang and Uwe Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 245–250, https://doi.org/10.5194/isprs-annals-IV-3-245-2018,https://doi.org/10.5194/isprs-annals-IV-3-245-2018, 2018

WATER SURFACE RECONSTRUCTION IN AIRBORNE LASER BATHYMETRY FROM REDUNDANT BED OBSERVATIONS

G. Mandlburger, N. Pfeifer, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 123–130, https://doi.org/10.5194/isprs-annals-IV-2-W4-123-2017,https://doi.org/10.5194/isprs-annals-IV-2-W4-123-2017, 2017

IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND DENSE IMAGE MATCHING

G. Mandlburger, K. Wenzel, A. Spitzer, N. Haala, P. Glira, and N. Pfeifer

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 259–266, https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017,https://doi.org/10.5194/isprs-annals-IV-2-W4-259-2017, 2017

A MOBILE MULTI-SENSOR PLATFORM FOR BUILDING RECONSTRUCTION INTEGRATING TERRESTRIAL AND AUTONOMOUS UAV-BASED CLOSE RANGE DATA ACQUISITION

A. Cefalu, N. Haala, S. Schmohl, I. Neumann, and T. Genz

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 63–70, https://doi.org/10.5194/isprs-archives-XLII-2-W6-63-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-63-2017, 2017

INVESTIGATION OF PARALLAX ISSUES FOR MULTI-LENS MULTISPECTRAL CAMERA BAND CO-REGISTRATION

J. P. Jhan, J. Y. Rau, N. Haala, and M. Cramer

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 157–163, https://doi.org/10.5194/isprs-archives-XLII-2-W6-157-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-157-2017, 2017

PROCESSING OF CRAWLED URBAN IMAGERY FOR BUILDING USE CLASSIFICATION

P. Tutzauer and N. Haala

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1-W1, 143–149, https://doi.org/10.5194/isprs-archives-XLII-1-W1-143-2017,https://doi.org/10.5194/isprs-archives-XLII-1-W1-143-2017, 2017

Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

C. H. Yang, Y. Pang, and U. Soergel

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1-W1, 35–42, https://doi.org/10.5194/isprs-annals-IV-1-W1-35-2017,https://doi.org/10.5194/isprs-annals-IV-1-W1-35-2017, 2017

HIGH DENSITY AERIAL IMAGE MATCHING: STATE-OF-THE-ART AND FUTURE PROSPECTS

N. Haala and S. Cavegn

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 625–630, https://doi.org/10.5194/isprs-archives-XLI-B4-625-2016,https://doi.org/10.5194/isprs-archives-XLI-B4-625-2016, 2016

USE AND OPTIMISATION OF PAID CROWDSOURCING FOR THE COLLECTION OF GEODATA

V. Walter, D. Laupheimer, and D. Fritsch

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 253–257, https://doi.org/10.5194/isprs-archives-XLI-B4-253-2016,https://doi.org/10.5194/isprs-archives-XLI-B4-253-2016, 2016

NETWORK DETECTION IN RASTER DATA USING MARKED POINT PROCESSES

A. Schmidt, C. Kruse, F. Rottensteiner, U. Soergel, and C. Heipke

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 701–708, https://doi.org/10.5194/isprs-archives-XLI-B3-701-2016,https://doi.org/10.5194/isprs-archives-XLI-B3-701-2016, 2016

WHICH 3D DATA REPRESENTATION DOES THE CROWD LIKE BEST? CROWD-BASED ACTIVE LEARNING FOR COUPLED SEMANTIC SEGMENTATION OF POINT CLOUDS AND TEXTURED MESHES

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