Gunho Sohn

York University, Earth and Space Science and Engineering, Faculty Member

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Phone: +1 416 650 8011
Address: Room 149, Petrie Science and Engineering Building, York University
4700 Keele Street, Toronto, ON M3J 1P3
Canada

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Beat Signer

Vrije Universiteit Brussel

James Elkins

School of the Art Institute of Chicago

Elif SERTEL

Istanbul Technical University

Maurizio Forte

Duke University

Armando Marques-Guedes

UNL - New University of Lisbon

Florin Curta

University of Florida

Fabio Cuzzolin

Oxford Brookes University

Davide Nadali

Università degli Studi "La Sapienza" di Roma

Gomaa Dawod

National Water Research center

Mustafa Zeybek

Selcuk University (Selçuk Üniversitesi)

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Papers by Gunho Sohn

Semantic Segmentation of Indoor Point Clouds Using Convolutional Neural Network

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Nov 13, 2017

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Progressive Modeling of 3D Building Rooftops from Airborne LiDAR and Imagery

Integration of Building Knowledge Into Binary Space Partitioning for the Reconstruction of Regularized Building Models

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Sep 30, 2015

Recent approaches for the automatic reconstruction of 3D building models from airborne point clou... more Recent approaches for the automatic reconstruction of 3D building models from airborne point cloud data integrate prior knowledge of roof shapes with the intention to improve the regularization of the resulting models without lessening the flexibility to generate all real-world occurring roof shapes. In this paper, we present a method to integrate building knowledge into the data-driven approach that uses binary space partitioning (BSP) for modeling the 3D building geometry. A retrospective regularization of polygons that emerge from the BSP tree is not without difficulty because it has to deal with the 2D BSP subdivision itself and the plane definitions of the resulting partition regions to ensure topological correctness. This is aggravated by the use of hyperplanes during the binary subdivision that often splits planar roof regions into several parts that are stored in different subtrees of the BSP tree. We therefore introduce the use of hyperpolylines in the generation of the BSP tree to avoid unnecessary spatial subdivisions, so that the spatial integrity of planar roof regions is better maintained. The hyperpolylines are shown to result from basic building roof knowledge that is extracted based on roof topology graphs. An adjustment of the underlying point segments ensures that the positions of the extracted hyperpolylines result in regularized 2D partitions as well as topologically correct 3D building models. The validity and limitations of the approach are demonstrated on real-world examples.

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A Novel Method for Extracting and Analyzing the Geometry Properties of the Shortest Pedestrian Paths Focusing on Open Geospatial Data

ISPRS International Journal of Geo-Information

Unlike car navigation, where almost all vehicles can traverse every route, one route might not be... more Unlike car navigation, where almost all vehicles can traverse every route, one route might not be optimal or even suitable for all pedestrians. Route geometry information, including tortuosity, twists and turns along roads, junctions, and road slopes, among others, matters a great deal for specific types of pedestrians, particularly those with limited mobility, such as wheelchair users and older adults. Offering practical routing services to these users requires that pedestrian navigation systems provide further information on route geometry. Therefore, this article proposes a novel method for extracting and analyzing the geometry properties of the shortest pedestrian paths, with a focus on open geospatial data across four aspects: (a) similarity, (b) route curviness, (c) road turns and intersections, and (d) road gradients. Deriving from the Hausdorff distance, a metric called the “dissimilarity ratio” was developed, allowing us to determine whether pairs of routes show any tendenc...

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Deep Convolutional Neural Network for Plume Rise Measurements in Industrial Environments

Estimating plume cloud height is essential for various applications, such as global climate model... more Estimating plume cloud height is essential for various applications, such as global climate models. Smokestack plume rise is the constant height at which the plume cloud is carried downwind as its momentum dissipates and the plume cloud and the ambient temperatures equalize. Although different parameterizations are used in most air-quality models to predict the plume rise, they have been unable to estimate it properly. This paper proposes a novel framework to monitor smokestack plume clouds and make long-term, real-time measurements of the plume rise. For this purpose, a three-stage framework is developed based on Deep Convolutional Neural Networks (DCNNs). In the first stage, an improved Mask R-CNN, called Deep Plume Rise Network (DPRNet), is applied to recognize the plume cloud. Then, image processing analysis and least squares theory are respectively used to detect the plume cloud’s boundaries and fit an asymptotic model into their centerlines. The y-component coordinate of this ...

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HDPV-SLAM: Hybrid Depth-augmented Panoramic Visual SLAM for Mobile Mapping System with Tilted LiDAR and Panoramic Visual Camera

arXiv (Cornell University), Jan 27, 2023

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Improving Cyclists’ Safety Using Intelligent Situational Awareness System

Sustainability

According to the World Health Organization (WHO), over 1.35 million people died in road traffic-r... more According to the World Health Organization (WHO), over 1.35 million people died in road traffic-related accidents worldwide in 2020 of which 41,000 are related to the cyclists. Bike safety is one of the most serious issues facing urban riders. According to Statistics Canada, this number represents 1654 cyclist deaths in Canada, an average of 74 deaths each year from 2006 to 2017. Cyclists are a critical component in traffic collisions, where they face a greater risk of serious injury or death. As a result, they are classified as vulnerable road users. To avoid this, the need for intelligent transportation systems (ITSs) that increase susceptible cyclists’ awareness of their surroundings is becoming apparent. As a result, we proposed a situational awareness system as part of ITS to enhance bike safety through the employment of three layers of applications: (1) the users tier (mobile application), (2) the virtual private server (VPS) and processing system, and (3) the database managem...

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RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR

2021 20th International Conference on Advanced Robotics (ICAR), 2021

A LiDAR-assisted panoramic visual simultaneous localization and mapping (SLAM) system for a mobil... more A LiDAR-assisted panoramic visual simultaneous localization and mapping (SLAM) system for a mobile mapping system (MMS) is presented in this paper. The feasibility research on the SLAM for MMS with a panoramic camera and a tilted LiDAR without GPS/IMU sparked our interest. Because of the significant disparity in spatial sensing coverage, we show that employing a panoramic camera as a primary sensor for SLAM is more suitable than using a tilted LiDAR in this particular sensor combination. Existing panoramic visual SLAM systems, on the other hand, produce up-to-scale results, making them inappropriate for many applications that require metrically-scaled results. We develop a panoramic visual SLAM system that uses LiDAR points to generate metrically-scaled outputs to address this constraint. First, the suggested SLAM system augments visual features with ranges generated from LiDAR points. Following that, the visual features are fed into the SLAM pipeline, which performs tracking, local mapping, and loop closing. Finally, the scale information in the ranges augmented to visual features is integrated into the SLAM pipeline via the production of metrically-scaled map points, eventually leading to metrically-scaled SLAM results. Extensive testing in challenging outdoor conditions has proven the effectiveness and robustness of the proposed SLAM system.

Determination of Regions Suitable for Agriculture in the Gordon Cosens Forest of Ontario by Means of Analytical Hierarchy Process with Fuzzy Logic Inference

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021

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Development of a High-Accuracy UAV-Photogrammetry Solution for Automated Environmental Modeling

This presentation is an overview of our methodologies and experiments in developing and implement... more This presentation is an overview of our methodologies and experiments in developing and implementing a UAVphotogrammetry system for accurate three-dimensional (3D) environmental modeling. The most significant components considered in the development of the system include in-house-built software solutions for: camera calibration, platform calibration, system integration, onboard data acquisition, multi-sensor control and flight/control-survey planning. In addition, a specific photogrammetric workflow is developed for 3D reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, appropriately adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a new method is proposed for robust sparse matching and linear estimation of two-view epipolar geometry. The key features of this approach compared to RANASC-like techniques include: evolutionary search instead of random sampling; guided sampling based on the spatial distr...

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Multilateration Under Flip Ambiguity for Uav Positioning Using Ultrawide-Band

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020

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Unmanned aerial image dataset: Ready for 3D reconstruction

Data in Brief, 2019

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The Environmental Applications of Wireless Sensor Networks

International Journal of Contents, 2007

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Towards Object Driven Floor Plan Extraction from Laser Point Cloud

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

During the last years, the demand for indoor models has increased for various purposes. As a prov... more During the last years, the demand for indoor models has increased for various purposes. As a provisional step to proceed towards higher dimensional indoor models, powerful and flexible floor plans can be utilised. Therefore, several methods have been proposed that provide automatically generated floor plans from laser point clouds. The prevailing methodology seeks to attain semantic enhancement of a model (e.g. the identification and labelling of its components) built upon already reconstructed (a priori) geometry. In contrast, this paper demonstrates preliminary research on the possibility to directly incorporate semantic knowledge, which is itself derived from the raw data during the extraction, into the geometric modelling process. In this regard, we propose a new method to automatically extract floor plans from raw point clouds. It is based on a hierarchical space partitioning of the data, integrated with primitive selection actuated by object detection. First, planar primitives...

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Matching Aerial Images to 3D Building Models Based on Context-Based Geometric Hashing

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

In this paper, a new model-to-image framework to automatically align a single airborne image with... more In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashin...

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Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection

Algorithms, 2017

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Revisiting Intrinsic Curves for Efficient Dense Stereo Matching

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

Dense stereo matching is one of the fundamental and active areas of photogrammetry. The increasin... more Dense stereo matching is one of the fundamental and active areas of photogrammetry. The increasing image resolution of digital cameras as well as the growing interest in unconventional imaging, e.g. unmanned aerial imagery, has exposed stereo image pairs to serious occlusion, noise and matching ambiguity. This has also resulted in an increase in the range of disparity values that should be considered for matching. Therefore, conventional methods of dense matching need to be revised to achieve higher levels of efficiency and accuracy. In this paper, we present an algorithm that uses the concepts of intrinsic curves to propose sparse disparity hypotheses for each pixel. Then, the hypotheses are propagated to adjoining pixels by label-set enlargement based on the proximity in the space of intrinsic curves. The same concepts are applied to model occlusions explicitly via a regularization term in the energy function. Finally, a global optimization stage is performed using belief-propagat...

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A complex document information processing prototype

Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 2006

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Edge Based 3D Indoor Corridor Modeling Using a Single Image

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015

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Robust Sparse Matching and Motion Estimation Using Genetic Algorithms

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015

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Semantic Segmentation of Indoor Point Clouds Using Convolutional Neural Network

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Nov 13, 2017

Download

Progressive Modeling of 3D Building Rooftops from Airborne LiDAR and Imagery

Integration of Building Knowledge Into Binary Space Partitioning for the Reconstruction of Regularized Building Models

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Sep 30, 2015

Download

A Novel Method for Extracting and Analyzing the Geometry Properties of the Shortest Pedestrian Paths Focusing on Open Geospatial Data

ISPRS International Journal of Geo-Information

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Deep Convolutional Neural Network for Plume Rise Measurements in Industrial Environments

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HDPV-SLAM: Hybrid Depth-augmented Panoramic Visual SLAM for Mobile Mapping System with Tilted LiDAR and Panoramic Visual Camera

arXiv (Cornell University), Jan 27, 2023

Download

Improving Cyclists’ Safety Using Intelligent Situational Awareness System

Sustainability

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RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR

2021 20th International Conference on Advanced Robotics (ICAR), 2021

Determination of Regions Suitable for Agriculture in the Gordon Cosens Forest of Ontario by Means of Analytical Hierarchy Process with Fuzzy Logic Inference

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021

Download

Development of a High-Accuracy UAV-Photogrammetry Solution for Automated Environmental Modeling

Download

Multilateration Under Flip Ambiguity for Uav Positioning Using Ultrawide-Band

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020

Download

Unmanned aerial image dataset: Ready for 3D reconstruction

Data in Brief, 2019

Download

The Environmental Applications of Wireless Sensor Networks

International Journal of Contents, 2007

Download

Towards Object Driven Floor Plan Extraction from Laser Point Cloud

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

Download

Matching Aerial Images to 3D Building Models Based on Context-Based Geometric Hashing

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

Download

Evolutionary Optimization for Robust Epipolar-Geometry Estimation and Outlier Detection

Algorithms, 2017

Download

Revisiting Intrinsic Curves for Efficient Dense Stereo Matching

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016

Download

A complex document information processing prototype

Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, 2006

Download

Edge Based 3D Indoor Corridor Modeling Using a Single Image

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015

Download

Robust Sparse Matching and Motion Estimation Using Genetic Algorithms

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015

Download

Gunho Sohn

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