Gunho Sohn

York University · Department of Earth and Space Science and Engineering (Faculty of Science and Engineering)

With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely...

The transmission lines are moving objects, which positions are dynamically affected by wind-induced conductor motion while they are acquired by airborne laser scanners. This wind effect results in a noisy distribution of laser points, which often hinders accurate representation of transmission lines and thus, leads to various types of modeling erro...

Recent research into improving the effectiveness of forest inventory management using airborne LiDAR data has focused on developing advanced theories in data analytics. Furthermore, supervised learning as a predictive model for classifying tree genera (and species, where possible) has been gaining popularity in order to minimize this labor-intensiv...

This paper aims to present a new approach for automatic extraction of building footprints in a combination of the IKONOS imagery with pan-sharpened multi-spectral bands and the low-sampled (∼ 0.1 points/m2) airborne laser scanning data acquired from the Optech's 1020 ALTM (Airborne Laser Terrain Mapper). Initially, a laser point cluster in 3D objec...

'Wikification of GIS by the masses' is a phrase-term first coined by Kamel Boulos in 2005, two years earlier than Goodchild's term 'Volunteered Geographic Information'. Six years later (2005-2011), OpenStreetMap and Google Earth (GE) are now full-fledged, crowdsourced 'Wikipedias of the Earth' par excellence, with millions of users contributing the...

The growing demand for high-resolution maps across various applications has underscored the necessity of accurately segmenting building vectors from overhead imagery. However, current deep neural networks often produce raster data outputs, leading to the need for extensive post-processing that compromises the fidelity, regularity, and simplicity of...

The growing demand for high-resolution maps across various applications has underscored the necessity of accurately segmenting building vectors from overhead imagery. However, current deep neural networks often produce raster data outputs, leading to the need for extensive post-processing that compromises the fidelity, regularity, and simplicity of...

The York University Teledyne Optech (YUTO) Mobile Mapping System (MMS) Dataset, encompassing four sequences totaling 20.1 km, was thoroughly assembled through two data collection expeditions on August 12, 2020, and June 21, 2019. Acquisitions were performed using a uniquely equipped vehicle, fortified with a panoramic camera, a tilted LiDAR, a Glob...

The combination of Remote Sensing and Deep Learning (DL) has brought about a revolution in converting digital surface models (DSMs) to digital terrain models (DTMs). DTMs are used in various fields, including environmental management, where they provide crucial topographical data to accurately model water flow and identify flood-prone areas. Howeve...

A growing trend for indoor localization is relying on the existing WiFi signal strength. However, this method faces challenges due to WiFi’s received signal strength (RSS) being susceptible to multipath, signal attenuation, and environmental variations, making it an unreliable measure of signal strength. To address this issue, a study was conducted...

LiDAR (Light Detection and Ranging) technology has remained popular in capturing natural and built environments for numerous applications. The recent technological advancements in electro-optical engineering have aided in obtaining laser returns at a higher pulse repetition frequency (PRF), which considerably increased the density of the 3D point c...

Creating virtual duplicates of the real world has garnered significant attention due to its applications in areas such as autonomous driving, urban planning, and urban mapping. One of the critical tasks in the computer vision community is semantic segmentation of outdoor collected point clouds. The development and research of robust semantic segmen...

The article addresses the need for a dependable and efficient computer vision system to examine utility networks with minimal human intervention, given the deteriorating state of these networks. To classify the dense and irregular point clouds obtained from the airborne laser terrain mapping (ALTM) system, which is used for data collection, we sugg...

Despite the computer vision community showing great interest in deep learning-based object detection, the adaptation to tree detection has been rare. There is a notable absence of proper datasets for automatic tree detection with deep convolutional neural networks to create and update tree inventories using LiDAR information. There are some publicl...

Due to the aged nature of much of the utility network infrastructure, developing a robust and trustworthy computer vision system capable of inspecting it with minimal human intervention has attracted considerable research attention. The airborne laser terrain mapping (ALTM) system quickly becomes the central data collection system among the numerou...

The Mobile Mapping System (MMS) plays a crucial role in generating accurate 3D maps for a wide range of applications. However, traditional MMS that utilizes tilted LiDAR (light detection and ranging) faces limitations in capturing comprehensive environmental data. We propose the “PVL-Cartographer” SLAM (Simultaneous Localization And Mapping) approa...

Determining the height of plume clouds is crucial for various applications, including global climate models. Smokestack plume rise refers to the altitude at which the plume cloud travels downwind until its momentum dissipates and the temperatures of the plume cloud and its surroundings become equal. While most air-quality models employ different pa...

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 t...

Mobile Mapping System (MMS) plays a crucial role in generating high-precision 3D maps for various applications. However, the traditional MMS that uses tilted LiDAR (light detection and ranging) has limitations in capturing complete information of the environment. To overcome these limitations, we propose a panoramic vision-aided Cartographer simult...

Due to the aged nature of much of the utility network infrastructure, developing a robust and trustworthy computer vision system capable of inspecting it with minimal human intervention has attracted considerable research attention. The airborne laser terrain mapping (ALTM) system quickly becomes the central data collection system among the numerou...

LiDAR (Light Detection and Ranging) technology has remained popular in capturing natural and built environments for numerous applications. The recent technological advancements in electro-optical engineering have aided in obtaining laser returns at a higher pulse repetition frequency (PRF), which considerably increased the density of the 3D point c...

The estimation of plume cloud height is essential for air-quality transport models, local environmental assessment cases, and global climate models. When pollutants are released by a smokestack, plume rise is the constant height at which the plume cloud is carried downwind as its momentum dissipates and the temperatures of the plume cloud and the a...

One essential feature of an autonomous train is minimizing collision risks with third-party objects. To estimate the risk, the control system must identify topological information of all the rail routes ahead on which the train can possibly move, especially within merging or diverging rails. This way, the train can figure out the status of potentia...

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 dea...

The size of the input receptive field is one of the most critical aspects in the semantic segmentation of the point cloud, yet it is one of the most overlooked parameters. This paper presents the multiple-input receptive field processing semantic segmentation network MRNet. The fundamental philosophy of our design is to overcome the size of the inp...

This paper proposes a novel visual simultaneous localization and mapping (SLAM), called Hybrid Depth-augmented Panoramic Visual SLAM (HDPV-SLAM), generating accurate and metrically scaled vehicle trajectories using a panoramic camera and a titled multi-beam LiDAR scanner. RGB-D SLAM served as the design foundation for HDPV-SLAM, adding depth inform...

The 3D information in Building Information Modeling (BIM) has received significant interest for smart city applications. Recently, employing Industry Foundation Classes (IFC) for BIM in data-driven methods for Building Energy Consumption Estimation (BECE) has gained momentum because of the enriched geometric and semantic information. However, despi...

Current consumer virtual reality (VR) systems rely heavily on handheld controllers for input. To this end, numerous methods have been developed and investigated since the emergence of VR in order to improve the user experience for interactions such as gaming or text entry while wearing a head-mounted display (HMD) and using handheld controllers [1,...

Deep learning has proved to be a breakthrough in depth generation. However, the generalization ability of deep networks is still limited, and they cannot maintain a satisfactory performance on some inputs. By addressing a similar problem in the segmentation field, a feature backpropagating refinement scheme (f-BRS) has been proposed to refine predi...

Deep learning, specifically the supervised approach, has proved to be a breakthrough in depth prediction. However, the generalization ability of deep networks is still limited, and they cannot maintain a satisfactory performance on some inputs. Addressing a similar problem in the segmentation field, a scheme (f-BRS) has been proposed to refine pred...

Establishing semantic interoperability between BIM and GIS is vital for geospatial information exchange. Semantic web have a natural ability to provide seamless semantic representation and integration among the heterogeneous domains like BIM and GIS through employing ontology. Ontology models can be defined (or generated) using domain-data represen...

The semantic integration modeling of BIM industry foundations classes and GIS City-geographic markup language are a milestone for many applications that involve both domains of knowledge. In this paper, we propose a system design architecture, and implementation of Extraction, Transformation and Loading (ETL) workflows of BIM and GIS model into RDF...

Nowadays, cities and buildings are increasingly interconnected with new modern data models like the 3D city model and Building Information Modelling (BIM) for urban management. In the past decades, BIM appears to have been primarily used for visualization. However, BIM has been recently used for a wide range of applications, especially in Building...

Analytical Hierarchy Process (AHP) with fuzzy logic inference on attributes was employed to determine areas most suitable for agriculture in the Gordon Cosens Forest (GCF) region within the District of Cochrane in northern Ontario, Canada. Attribute layers considered were soil texture, ELC (Ecological Land Classification) moisture regime, slope, ca...

Data represented in the form of geospatial context and detailed building information are prominently nurturing infrastructure development and smart city applications. Bringing open-formats from data acquisition level to information engineering accelerates geospatial technologies towards urban sustainability and knowledge-based systems. BIM and GIS...

LiDAR (Light Detection and Ranging) mounted with static and mobile vehicles has been rapidly adopted as a primary sensor for mapping natural and built environments for a range of civil and military applications. Recently, technology advancement in electro-optical engineering enables acquiring laser returns at high pulse repetition frequency (PRF) f...

Thanks to the proliferation of commodity 3D devices such as HoloLens, one can have easy access to the 3D model of indoor building objects. However, this model does not match 2D available computer-aided design (CAD) models as the as-built model. To address this problem, in this study, a 3-step registration method is proposed. First, binary images, i...

Ultrawide-band (UWB) ranging technology and multilateration techniques have recently been emerging solutions for positioning unmanned aerial vehicles (UAVs) in GNSS-denied environments. This solution offers cm-level ranging accuracy and considerable robustness to multipath receptions. UWB modules are commonly used in an anchor-based configuration;...

In recent years, an ever-increasing number of remote satellites are orbiting the Earth which streams vast amount of visual data to support a wide range of civil, public and military applications. One of the key information obtained from satellite imagery is to produce and update spatial maps of built environment due to its wide coverage with high r...

Indoor localization has attracted the attention of researchers for wide applications in areas like construction, facility management, industries, logistics, and health. The Received Signal Strength (RSS) based fingerprinting method is widely adopted because it has a lower cost over other methods. RSS is a measurement of the power present in the rec...

In this paper, we introduced a recently developed image-based model alignment technique for 3D reconstruction of large-scale indoor corridors. The proposed participatory model alignment technique enables crowd source single image-based modeling since it allows various participants to incorporate their images taken from different cameras for large-s...

In recent years, an ever-increasing number of remote satellites are orbiting the Earth which streams vast amount of visual data to support a wide range of civil, public and military applications. One of the key information obtained from satellite imagery is to produce and update spatial maps of built environment due to its wide coverage with high r...

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 exis...

A network of railway infrastructure is one of the most critical infrastructure assets for supporting the national economy and sustainable mobility. Safe and reliable maintenance of railway infrastructure is critical to ensure that rail systems run safely and punctually. Such maintenance requires regular surveying of railway assets, which typically...

Unmanned aerial vehicles (UAVs) have become popular platforms for collecting various types of geospatial data for various mapping, monitoring and modelling applications. With the advancement of imaging and computing technologies, a vast variety of photogrammetric, computer-vision and, nowadays, end-to-end learning workflows are introduced to produc...

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 i...

One of the most active areas of research in photogrammetry and computer vision is dense three-dimensional (3D) reconstruction of the environment via high-density image matching. This research interest is mainly driven by the growing popularity of unconventional imaging solutions such as images captured from unmanned aerial vehicles. With such data,...

A SEMANTIC GRAPH DATABASE FOR BIM-GIS INTEGRATED INFORMATION MODEL FOR AN INTELLIGENT URBAN MOBILITY WEB APPLICATION

Over the recent years, the usage of semantic web technologies and Resources Description Framework (RDF) data models have been notably increased in many fields. Multiple systems are using RDF data to describe information resources and semantic associations. RDF data plays a very important role in advanced information retrieval, and graphs are effici...

With the increasing number and usage of mobile devices in people’s daily life, indoor positioning has attracted a lot attention from both academia and industry for the purpose of providing location-aware services. This work proposes an indoor positioning system, primarily based on WLAN fingerprint matching, that includes various minor improvements...

Over the recent years, the usage of semantic web technologies and Resources Description Framework (RDF) data models have been notably increased in many fields. Multiple systems are using RDF data to describe information resources and semantic associations. RDF data plays a very important role in advanced information retrieval, and graphs are effici...

Urban and population growth results in increasing pressure on the public utilities like transport, energy, healthcare services, crime management and emergency services in the realm of smart city management. Smart management of these services increases the necessity of dealing with big data which is come from different sources with various types and...

The goal for our paper is to classify tree genera using airborne Light Detection and Ranging (LiDAR) data with Convolution Neural Network (CNN) – Multi-task Network (MTN) implementation. Unlike Single-task Network (STN) where only one task is assigned to the learning outcome, MTN is a deep learning architect for learning a main task (classification...

In this paper, we extend a recently proposed visual Simultaneous Localization and Mapping (SLAM) techniques, known as Layout SLAM, to make it robust against error accumulations, abrupt changes of camera orientation and miss-association of newly visited parts of the scene to the previously visited landmarks. To do so, we present a novel technique of...

As Building Information Modelling (BIM) thrives, geometry becomes no longer sufficient; an ever increasing variety of semantic information is needed to express an indoor model adequately. On the other hand, for the existing buildings, automatically generating semantically enriched BIM from point cloud data is in its infancy. The previous research t...

We propose a real time indoor corridor layout estimation method based on visual Simultaneous Localization and Mapping (SLAM). The proposed method adopts the Manhattan World Assumption at indoor spaces and uses the detected single image straight line segments and their corresponding orthogonal vanishing points to improve the feature matching scheme...

In this paper, a robust technique based on a genetic algorithm is proposed for estimating two-view epipolar-geometry of uncalibrated perspective stereo images from putative correspondences containing a high percentage of outliers. The advantages of this technique are three-fold: (i) replacing random search with evolutionary search applying new stra...

Railways have been used as one of the most crucial means of transportation in public mobility and economic development. For safe railway operation, the electrification system in the railway infrastructure, which supplies electric power to trains, is an essential facility for stable train operation. Due to its important role, the electrification sys...

Railway has been used as one of the most crucial means of transportation in public mobility and economic development. For efficiently operating railways, the electrification system in railway infrastructure, which supplies electric power to trains, is essential facilities for stable train operation. Due to its important role, the electrification sy...

In recent years, 3D virtual indoor/outdoor urban modelling becomes a key spatial information framework for many civil and engineering applications such as evacuation planning, emergency and facility management. For accomplishing such sophisticate decision tasks, there is a large demands for building multi-scale and multi-sourced 3D urban models. Cu...

In recent years, 3D virtual indoor/outdoor urban modelling becomes a key spatial information framework for many civil and engineering applications such as evacuation planning, emergency and facility management. For accomplishing such sophisticate decision tasks, there is a large demands for building multi-scale and multi-sourced 3D urban models. Cu...

Since people spend most of their time indoors, their indoor activities and related issues in health, security and energy consumption have to be understood. Hence, gathering and representing spatial information of indoor spaces in form of 3D models become very important. Considering the available data gathering techniques with respect to the sensors...

Since people spend most of their time indoors, their indoor activities and related issues in health, security and energy consumption have to be understood. Hence, gathering and representing spatial information of indoor spaces in form of 3D models become very important. Considering the available data gathering techniques with respect to the sensors...

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 th...

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 th...

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 acc...