Impyeong Lee

Developing a UAV-based Rapid Mapping System for Emergency Response

As disasters and accidents due to various natural or artificial causes being increased, the demands for rapid responses for emergency situations also have been ever-increasing. These emergency responses need to be not only more intelligent but also more customized to the individual sites to manage the emergency situations more efficiently. More effective counter-measures in such situations will be established only if more accurate and prompt spatial information about the changing areas due to the emergency are available. This information can be rapidly extracted from the airborne sensory data acquired by a UAV-based rapid mapping system. This paper introduces a Korean national project to develop a UAV-based rapid mapping system. The overall budget is about 6 million US dollars and the period is about four years. The goal of this project is to develop a light and flexible system at low cost to perform rapid mapping for emergency responses. This system consists of two main parts, aerial part and ground part. The aerial part includes a small UAV platform equipped with sensors (GPS/IMU/Camera/Laser Scanner) and sensor supporting modules for sensor integration, data transmission to the ground, data storages, time synchronization, and sensor stabilization. The ground part includes three sub-systems with appropriate software, which are a control/receiving/archiving subsystem, a data georeferencing subsystem, and a spatial information generation subsystem. As being in a middle stage of this project, we will present a brief introduction to the overall project and the design of the aerial system with its verification results.

Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

As LADAR systems applications gradually become more diverse, new types of systems are being developed. When developing new systems, simulation studies are an essential prerequisite. A simulator enables performance predictions and optimal system parameters at the design level, as well as providing sample data for developing and validating application algorithms. The purpose of the study is to propose a method for simulating a Geiger-mode imaging LADAR system. We develop simulation software to assess system performance and generate sample data for the applications. The simulation is based on three aspects of modeling—the geometry, radiometry and detection. The geometric model computes the ranges to the reflection points of the laser pulses. The radiometric model generates the return signals, including the noises. The detection model determines the flight times of the laser pulses based on the nature of the Geiger-mode detector. We generated sample data using the simulator with the system parameters and analyzed the detection performance by comparing the simulated points to the reference points. The proportion of the outliers in the simulated points reached 25.53%, indicating the need for efficient outlier elimination algorithms. In addition, the false alarm rate and dropout rate of the designed system were computed as 1.76% and 1.06%, respectively.

Translation-Based KLT Tracker Under Severe Camera Rotation Using GPS/INS Data

The Kanade-Lucas-Tomasi (KLT) faces a significant challenge with a translation model when the camera undergoes severe rotation. Although the use of an affine model can overcome this challenge, it is computationally expensive. In this letter, two solutions are proposed. Given reliable GPS/INS data, we determine the rotation angle between a stereo frame and use this knowledge to enhance the translation-based KLT tracker to remain robust under this situation. The experimental results on five pairs of UAV images show that the proposed methods can achieve equivalent tracking efficacy as the affine model while the computational cost remains close to that of the translation model.

A Sequential Aerial Triangulation Algorithm for Real-time Georeferencing of Image Sequences Acquired by an Airborne Multi-Sensor System

Real-time image georeferencing is essential to the prompt generation of spatial information such as orthoimages from the image sequence acquired by an airborne multi-sensor system. It is mostly based on direct georeferencing using a GPS/INS system, but its accuracy is limited by the quality of the GPS/INS data. More accurate results can be acquired using traditional aerial triangulation (AT) combined with GPS/INS data, which can be performed only as a post-processing method due to intense computational requirements. In this study, we propose a sequential AT algorithm that can produce accurate results comparable to those from the simultaneous AT algorithm in real time. Whenever a new image is added, the proposed algorithm rapidly performs AT with minimal computation at the current stage using the computational results from the previous stage. The experimental results show that the georeferencing of an image sequence at any stage took less than 0.1 s and its accuracy was determined within ± 5 cm on the estimated ground points, which is comparable to the results of simultaneous AT. This algorithm may be used for applications requiring real-time image georeferencing such as disaster monitoring and image-based navigation.

Data simulation of an airborne lidar system

An airborne LIDAR (LIght Detection And Ranging) system can rapidly generate 3D points by densely sampling the terrain surfaces using laser pulses. The LIDAR points can be efficiently utilized for automatic reconstruction of 3D models of the objects on the terrain and the terrain itself. The data simulation of such a LIDAR system is significantly useful not only to design an optimal sensor for a specific application but also to assess data processing algorithms with various kinds of test data. In this study, we thus attempted to develop data simulation software of an airborne LIDAR system generally consisting of a GPS, an IMU and a laser scanner. We focused particularly on the geometric modeling of the sensors and the object modeling of the targets and background. Hence the data simulation software has been developed using these models. For the geometric modeling, we derived the sensor equation by modeling not only the geometric relationships between the three modules, such as a GPS, an IMU and a laser scanner but also the systematic errors associated with them. Moreover, for rapid and effective simulation, we designed the data model for both targets and background. We constructed the model data by converting the VRML formatted data into the designed model and stored these data in a 3D spatial database that can offer more effective 3D spatial indexing and query processing. Finally, we developed a program that generates simulated data along with the system parameters of a sensor, a terrain model and its trajectories over the model given.

An alternative measure of public transport accessibility based on space syntax

The local governments of major cities in Korea are giving focus on public transportation to reduce congestion and improve accessibility in city areas. In this regards, the proper measurement of accessibility is now a key policy requirement for reorganizing the public transport network. However, Public transport routing problems are considered to be highly complicated since a multi-mode travel generates different combinations of accessibility. While most of the previous research efforts on measuring transport accessibility are found at zone-levels, an alternative approach at a finer scale such as bus links and stops is presented in this study. We propose a method to compute the optimal route choice of origin-destination pairs and measure the accessibility of the chosen mode combination based on topological configuration. The genetic algorithm is used for the computation of the journey paths, whereas the space syntax theory is used for the accessibility. The resulting accessibilities of bus stops are calibrated by O-D survey data and the proposed process is tested on a CBD of Seoul using the city GIS network data.

CCTV Coverage Index Based on Surveillance Resolution and Its Evaluation Using 3D Spatial Analysis

We propose a novel approach to evaluating how effectively a closed circuit television (CCTV) system can monitor a targeted area. With 3D models of the target area and the camera parameters of the CCTV system, the approach produces surveillance coverage index, which is newly defined in this study as a quantitative measure for surveillance performance. This index indicates the proportion of the space being monitored with a sufficient resolution to the entire space of the target area. It is determined by computing surveillance resolution at every position and orientation, which indicates how closely a specific object can be monitored with a CCTV system. We present full mathematical derivation for the resolution, which depends on the location and orientation of the object as well as the geometric model of a camera. With the proposed approach, we quantitatively evaluated the surveillance coverage of a CCTV system in an underground parking area. Our evaluation process provided various quantitative-analysis results, compelling us to examine the design of the CCTV system prior to its installation and understand the surveillance capability of an existing CCTV system.

Georeferencing of Indoor Omni-Directional Images Acquired by a Rotating Line Camera

To utilize omni-directional images acquired by a rotating line camera for indoor spatial information services, we should register precisely the images with respect to an indoor coordinate system. In this study, we thus develop a georeferencing method to estimate the exterior orientation parameters of an omni-directional image - the position and attitude of the camera at the acquisition time. First, we derive the collinearity equations for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the exterior orientation parameters using the collinearity equations with indoor control points. The experimental results from the application to real data indicate that the exterior orientation parameters is estimated with the precision of 1.4 mm and for the position and attitude, respectively. The residuals are within 3 and 10 pixels in horizontal and vertical directions, respectively. Particularly, the residuals in the vertical direction retain systematic errors mainly due to the lens distortion, which should be eliminated through a camera calibration process. Using omni-directional images georeferenced precisely with the proposed method, we can generate high resolution indoor 3D models and sophisticated augmented reality services based on the models.

NEW AFFINE TRANSFORMATION PARAMETERS FOR THE HORIZONTAL NETWORK OF SEOUL/KOREA BY MULTIVARIATE TLS-ADJUSTMENT

Abstract The new approach of multivariate Total Least-Squares (TLS) adjustment has been applied to 33 stations of the horizontal network of Seoul/Korea in order to estimate best-fitting affine transformation parameters. The results are presented along with variances and covariances (in first order approximation), and comparisons are drawn with the standard Least-Squares (LS) approach. Although the estimates from TLS do not show practical differences with respect to LS, the fit does yield significant improvements. Furthermore, the estimates could be substantially different when the data quality drops considerably. No weights are taken into consideration at this time.

High accurate affordable car navigation using built-in sensory data and images acquired from a front view camera

Nowadays cars are equipped with various built-in sensors such as speedometers, odometers, accelerometers, and gyros for safety and maintenance. Also, front view images can be economically acquired by a low-cost camera available in smartphones or black boxes. The combination of the built-in sensory data and the images can be an effective complement to a GPS based navigation. Therefore, we propose a car navigation framework to determine car position and attitude using the built-in sensory data such as a speed, angular rate and the images from a front view camera. The method consists of three steps, 1) dead reckoning using the velocity and yaw rate provided in real-time, 2) image georeferencing based on a sequential bundle adjustment using the dead reckoning results and 3) final estimation using a Kalman filter with the georeferencing results. The experimental results show that the proposed method can provide the positions with a reasonable accuracy level, which can be meaningful to complement a traditional GPS based navigation with a low cost.