Publications

@article{doi:10.1177/0361198119896783,

title = {Public Transit Service Reliability Assessment using Two-Fluid Model},

author = {Seungho Yang and Afnan Ahmad and Peter Y Park and Gunho Sohn and Jeremy Krygsman},

url = {https://doi.org/10.1177/0361198119896783},

doi = {10.1177/0361198119896783},

year  = {2020},

date = {2020-01-01},

journal = {Transportation Research Record},

volume = {2674},

number = {4},

pages = {89-100},

abstract = {This study introduces a traffic flow theory-based reliability indicator to evaluate the inter-city public transit service. The two-fluid theory parameter n that measures the road networks’ resilience to changing traffic is used as a new reliability indicator of public bus service. We compared the performance of the new indicator with the three existing reliability indicators, including on-time performance, with a total of 52 different GO Bus routes to ascertain the usability of the new indicator. The GO Bus service is an inter-city bus service operated by Metrolinx in the Greater Toronto and Hamilton areas in Ontario, Canada. We used 1 month of GO Bus GPS data collected in July 2017 to estimate various public transit reliability indictors. We also investigated the relationship between reliability indicators and selected roadway network characteristics, such as route length, freeway ratio, intersection density along a route, and so forth. The study applied a series of statistical analyses, including principal component analysis, correlation analysis, and z-test using Fisher’s z transformation. The results showed that the proposed two-fluid indicator n can be used as a supplementary reliability indicator for assessing road networks’ resilience in regards to changing traffic flow conditions. The new indicator provided additional insights for inter-city bus service operators for initiating communication with roadway governing agencies for the purpose of improving road networks to further improve public transit service reliability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{SHAHBAZI2019103962,

title = {Unmanned aerial image dataset: Ready for 3D reconstruction},

author = {Mozhdeh Shahbazi and Patrick Ménard and Gunho Sohn and Jérôme Théau},

url = {http://www.sciencedirect.com/science/article/pii/S2352340919303154},

doi = {https://doi.org/10.1016/j.dib.2019.103962},

issn = {2352-3409},

year  = {2019},

date = {2019-01-01},

journal = {Data in Brief},

volume = {25},

pages = {103962},

keywords = {Bundle adjustment, Dense matching, Stereo, Structure from motion, Unmanned Aerial Vehicle},

pubstate = {published},

tppubtype = {article}

}

@article{Chen2019MultiScaleHC,

title = {Multi-Scale Hierarchical CRF for Railway Electrification Asset Classification From Mobile Laser Scanning Data},

author = {Leihan Chen and Jaewook Jung and Gunho Sohn},

url = {https://ieeexplore.ieee.org/document/8733888},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},

volume = {12},

pages = {3131-3148},

keywords = {Context modeling, Inspection, Lasers, Rail transportation, Task analysis, Three-dimensional displays, Wires},

pubstate = {published},

tppubtype = {article}

}

@article{JUNG2019157,

title = {A line-based progressive refinement of 3D rooftop models using airborne LiDAR data with single view imagery},

author = {Jaewook Jung and Gunho Sohn},

url = {http://www.sciencedirect.com/science/article/pii/S0924271619300036},

doi = {https://doi.org/10.1016/j.isprsjprs.2019.01.003},

issn = {0924-2716},

year  = {2019},

date = {2019-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {149},

number = {0924-2716},

pages = {157 - 175},

abstract = {In recent years, many mega-cities have provided 3D photorealistic virtual models, a digital replica of the geometrical structures of cities, for more effective decision support in public safety, urban planning, and engineering applications. Most research attempts at reconstructing geometric models of cities treat such urban systems as if they are in a static environment. However, cities are dynamic systems that continuously change over time. Accordingly, their virtual representations need to be regularly updated in a timely manner to allow for accurate analysis. The concept of progressive city modelling is to continuously reconstruct city models by accommodating changes recognized in the spatio-temporal domain, while preserving unchanged structures. This paper proposes a novel fusion method to progressively refine building rooftop models over time by integrating multi-sensor data. The proposed method integrates the line modelling cues of existing rooftop models produced by airborne laser scanning data with the new ones extracted from optical imagery. This modelling cue integration process is developed to progressively rectify geometric errors based on Hypothesize and Test optimization using Minimum Description Length. A stochastic method, Markov Chain Monte Carlo, coupled with simulated annealing, is employed to generate model hypotheses and perform a global optimization for finding the best solution. This fusion method is designed to offset the limitations of respective sensors and thus rectify various modelling errors (shape deformation, boundary displacement, and orientation errors) that are often involved in rooftop building models. The performance evaluation tested over the ISPRS show the proposed modelling method can achieve the improvements of 1.8%, 0.54°, 0.33 m, and 0.007 for the quality, orientation difference, Hausdorff distance, and turning function distance, respectively, compared with initial building models. In addition, the proposed methods show the highest performance in the quality measure among the state of the art methods, while demonstrates competitive performance in the completeness and correctness measures.},

keywords = {Airborne imagery, Airborne laser scanning, Continuous modelling, Model selection, Rooftop modelling},

pubstate = {published},

tppubtype = {article}

}

@article{2018JPRS..146..373S,

title = {High-density stereo image matching using intrinsic curves},

author = {Mozhdeh Shahbazi and Gunho Sohn and Jérôme Théau},

doi = {10.1016/j.isprsjprs.2018.10.005},

year  = {2018},

date = {2018-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {146},

pages = {373-388},

keywords = {Dense matching, Disparity search space, Energy function, Intrinsic curves, Occlusion, Optimization},

pubstate = {published},

tppubtype = {article}

}

@article{articlec,

title = {Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection},

author = {Mozhdeh Shahbazi and Gunho Sohn and Jérôme Théau},

doi = {10.3390/a10030087},

year  = {2017},

date = {2017-01-01},

journal = {Algorithms},

volume = {10},

pages = {87},

keywords = {Adaptive thresholding, Epipolar geometry, Evolutionary search, Genetic algorithm, Guided sampling, Outlier detection, Sparse matching},

pubstate = {published},

tppubtype = {article}

}

@article{articled,

title = {Robust Structure-from-Motion Computation: Application to Open-Pit Mine Surveying from Unmanned Aerial Images},

author = {Mozhdeh Shahbazi and Gunho Sohn and Jérôme Théau and Patrick Ménard},

doi = {10.1139/juvs-2016-0027},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Unmanned Vehicle Systems},

keywords = {Genetic algorithm, Mapping, Mining, Self-calibration, Sparse bundle adjustment, Structure-from-motion, successive reconstruction, Unmanned aerial imagery},

pubstate = {published},

tppubtype = {article}

}

@article{articlee,

title = {Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data},

author = {Jaewook Jung and Yoonseok Jwa and Gunho Sohn},

doi = {10.3390/s17030621},

year  = {2017},

date = {2017-01-01},

journal = {Sensors},

volume = {17},

keywords = {3D building rooftop modeling, Airborne laser scanning data, Building reconstruction, Minimum description length, Regularization},

pubstate = {published},

tppubtype = {article}

}

@article{articlef,

title = {Wind adaptive modeling of transmission lines using minimum description length},

author = {Yoonseok Jwa and Gunho Sohn},

doi = {10.1016/j.isprsjprs.2017.01.013},

year  = {2017},

date = {2017-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {125},

pages = {193-206},

keywords = {3D transmission line model, Airborne laser scanning data, Hypothesis-verification, Minimum description length, Regression analysis, Splitting-merging, Wind blowing effect},

pubstate = {published},

tppubtype = {article}

}

@article{articlei,

title = {Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing},

author = {Jaewook Jung and Gunho Sohn and Ki In Bang and Andreas Wichmann and Costas Armenakis and Martin Kada},

doi = {10.3390/s16060932},

year  = {2016},

date = {2016-01-01},

journal = {Sensors},

volume = {16},

pages = {932},

keywords = {3D Building Models, Aerial Imagery, Geometric Hashing, Model to Image Matching, Registration},

pubstate = {published},

tppubtype = {article}

}

@article{articlej,

title = {Maximizing the Diversity of Ensemble Random Forests for Tree Genera Classification Using High Density LiDAR Data},

author = {Connie Ko and Gunho Sohn and Tarmo Remmel and John Miller},

doi = {10.3390/rs8080646},

year  = {2016},

date = {2016-01-01},

journal = {Remote Sensing},

volume = {8},

keywords = {Ensemble Classification; Diversity Maximization, lidar, Random Forests, Tree Genera Classification},

pubstate = {published},

tppubtype = {article}

}

@article{articlel,

title = {Geometric Context and Orientation Map Combination for Indoor Corridor Modeling Using a Single Image},

author = {Ali Baligh Jahromi and Gunho Sohn},

doi = {10.5194/isprsarchives-XLI-B4-295-2016},

year  = {2016},

date = {2016-01-01},

journal = {ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},

volume = {XLI-B4},

pages = {295-302},

keywords = {Geometric Context, Hypothesis-verification, Indoor Model Reconstruction, Scene Layout Parameterization},

pubstate = {published},

tppubtype = {article}

}

@article{articlem,

title = {Towards Object Driven Floor Plan Extraction from Laser Point Cloud},

author = {Kivanc Babacan and Jaewook Jung and Andreas Wichmann and B Jahromi and Mozhdeh Shahbazi and Gunho Sohn and Martin Kada},

doi = {10.5194/isprsarchives-XLI-B3-3-2016},

year  = {2016},

date = {2016-01-01},

journal = {ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},

volume = {XLI-B3},

pages = {3-10},

keywords = {Door Detection, floor plan, Indoor Modelling, Mobile Laser, Point Cloud, Reconstruction},

pubstate = {published},

tppubtype = {article}

}

@article{articlen,

title = {Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling},

author = {Mozhdeh Shahbazi and Gunho Sohn and Jérôme Théau and Patrick Menard},

doi = {10.3390/s151127493},

year  = {2015},

date = {2015-01-01},

journal = {Sensors},

volume = {15},

pages = {27493-27524},

keywords = {Calibration, Georeferencing, Ground Control Point, Mine, Modeling, Photogrammetry, UAV},

pubstate = {published},

tppubtype = {article}

}

@article{articleo,

title = {Automatic Co-Registration of Pan-Tilt-Zoom (PTZ) Video Images with 3D Wireframe Models},

author = {Ravi Persad and Costas Armenakis and Gunho Sohn},

doi = {10.14358/PERS.81.11.847},

year  = {2015},

date = {2015-01-01},

journal = {Photogrammetric Engineering and Remote Sensing},

volume = {81},

pages = {847-859},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{isprs-archives-XL-3-W2-197-2015,

title = {Robust Sparse Matching and Motion Estimation Using Genetic Algorithms},

author = {Mozhdeh Shahbazi and Gunho Sohn and Jérôme Théau and Patrick Ménard},

url = {https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-3-W2/197/2015/},

doi = {10.5194/isprsarchives-XL-3-W2-197-2015},

year  = {2015},

date = {2015-01-01},

journal = {ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},

volume = {XL-3/W2},

pages = {197--204},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articler,

title = {Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data},

author = {Connie Ko and Gunho Sohn and Tarmo Remmel and John Miller},

doi = {10.3390/rs61111225},

year  = {2014},

date = {2014-01-01},

journal = {Remote Sensing},

volume = {6},

pages = {11225-11243},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articles,

title = {A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada},

author = {Junjie Zhang and Gunho Sohn and Mathieu Brédif},

doi = {10.1016/j.isprsjprs.2014.08.007},

year  = {2014},

date = {2014-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {98},

pages = {44–57},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlet,

title = {Classification of airborne laser scanning data using JointBoost},

author = {Bo Guo and Xianfeng Huang and Fan Zhang and Gunho Sohn},

doi = {10.1016/j.isprsjprs.2014.03.004},

year  = {2014},

date = {2014-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {92},

pages = {124–136},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articleu,

title = {Railway Object Recognition Using Mobile Laser Scanning Data},

author = {Chao Luo and Yoon Jwa and Gunho Sohn and Jong Won and Suk Lee},

doi = {10.9723/jksiis.2014.19.2.085},

year  = {2014},

date = {2014-01-01},

journal = {Journal of the Korea Industrial Information System Society},

volume = {19},

pages = {85-91},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlev,

title = {Theme section “Urban object detection and 3D building reconstruction”},

author = {Franz Rottensteiner and Gunho Sohn and Markus Gerke and Jan Wegner},

doi = {10.1016/j.isprsjprs.2014.04.009},

year  = {2014},

date = {2014-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {93},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{articlew,

title = {Results of the ISPRS benchmark on urban object detection and 3D building reconstruction},

author = {Franz Rottensteiner and Gunho Sohn and Markus Gerke and Jan Wegner and Uwe Breitkopf and Jaewook Jung},

doi = {10.1016/j.isprsjprs.2013.10.004},

year  = {2014},

date = {2014-01-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {93},

pages = {256-271},

keywords = {},

pubstate = {published},

tppubtype = {article}

}