Jungwon Kang

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

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...

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...

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...

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;...

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...

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, we present a new algorithm for fast online motion segmentation with low time complexity. Feature points in each input frame of an image stream are represented as a spatial neighbor graph. Then, the affinities for each point pair on the graph, as edge weights, are computed through our effective motion analysis based on multi-temporal...

This paper deals with the improvement of clustering results by enhancing performance of sampling. The proposed clustering framework is established on a J-linkage framework [4] with guided sampling technique for multi-structures [7]. We tested the proposed method on publicly available dataset, verifying the validness of the proposed method.

In this paper, we describe a probabilistic voxel mapping algorithm using an adaptive confidence measure of stereo matching. Most of the 3D mapping algorithms based on stereo matching usually generate a map formed by point cloud. There are many reconstruction errors. The reconstruction errors are due to stereo reconstruction error factors such as ca...

This paper presents a method for pixel-wise segmentation of moving re-gions using sparse motion cues on an image from a freely moving camera. The main idea is to utilize residual motion, i.e., motion relative to a background, on sparse grid points. Our algorithm consists of three parts: global motion estimation, character-ization of points based on...

We present a method for online motion segmentation in dynamic scenes. Here the dynamic scene is a scene without restrictions on the motion of objects and the motion of a camera. Such a scene causes complex interaction of objects and a camera, leading to the generation of trajectories corrupted by noise and outliers. Moreover, no prior knowledge of...

The aim of this study is to estimate 6D robot pose. We estimate 6D robot pose using GPS (Global IMU(Inertial Measurement System) in outdoor. We proposed reliability method for 6D robot pose. We get 3D mapping results and compare the 3D mapping results with and without our method. The 3D mapping results with our method was more accurate.

This paper deals with a problem of 3D world reconstruction and independently moving point detection using stereo vision. Our algorithm reconstructs 3D world through dense stereo matching, triangulation at local frame, and registration in world frame. In addition, independently moving points are detected by geometric constraints. We have tested our...

In this paper, we propose a independently moving feature detection algorithm using monocular vision. The proposed algorithm can detect independently moving feature points from all of the feature points by geometric constraints. The geometric constraints consist of epipolar constraint and trifocal constraint. The proposed algorithm can be implemente...

The detection of free space and obstacles in a scene is essential for safe driving. Among sensors for environment perception, a stereo-vision is promising as it provides 3D perception information. Moreover current decreasing price of a camera module makes a vision sensor attractive, taking into account the consumer product. In this paper we propose...

This paper introduces our mobile platform, which equips multiple sensors for 3D outdoor world modeling. The data from GPS and IMU on the platform are fused to provide vehicle pose on the ground. The laterally installed LRFs(Laser Range Finder) on each side of the vehicle give environment perception information. The data from the LRFs are fused with...

There has been significant research into the development of 3D world modeling techniques that are important requisite for intelligent vehicle navigation. In this paper we describe 3D world modeling process to represent the environment of an intelligent vehicle. We can generate more robust stereo matching results by switchable stereo matching techni...

This paper describes the research results on an indoor robot navigation system using visual features extracted from ceiling images of a large building environment. To reduce the cost and complexity of the system, we developed a single camera-based system that utilizes ceiling images acquired from a camera installed to point upwards. To make the ope...

3D perception of an environment is essential for robot navigation. In this paper, we propose a dense stereo matching algorithm that works well with a scene with large depth variation, and can also operate in real-time. Our method assigns weights to pixels in a support window based on in-tensity gradient analysis and geometric proximity. The selecte...