• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.479-484
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• 2020

Foreign object debris (FOD) is a generic term for all substances that may pose a threat to aircraft operations on a runway. In the past, FOD detection and collection methods using human resources were very inefficient in terms of efficiency and economics, so it is essential to develop an unmanned FOD detection system suitable for domestic use. In this paper, the fixed FOD automatic detection system and mobile FOD automatic detection system using EO camera and radar were studied and developed at the Taean airfield of Hanseo University, and fixed and mobile method were operated to confirm that automatic FOD detection in the runway of the airfield is possible regardless of illumination and weather conditions.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.182-189
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• 2023

Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.47-57
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• 2024

This paper proposes a system to efficiently manage delays caused by unmanaged and congested queues in crowded environments. Such queues not only cause inconvenience but also pose safety risks. Existing systems, relying on single-camera feeds, are inadequate for complex scenarios requiring multiple cameras. To address this, we developed a multi-vision long queue detection system that integrates multiple vision algorithms to accurately detect various types of queues. The algorithm processes real-time video data from multiple cameras, stitching overlapping segments into a single panoramic image. By combining object detection, tracking, and position variation analysis, the system recognizes long queues in crowded environments. The algorithm was validated with 96% accuracy and a 92% F1-score across diverse settings.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.486-492
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• 2006

본 논문에서는 비디오에서의 특징점 추적을 통해 얻은 2D 좌표를 이용한 3D 구조를 추정하는 방법과 네 점 이상의 공통점을 이용한 융합 방법을 제안한다. 영상의 각 프레임에서 공통되는 특징점을 이용하여 형상을 추정한다. 영상의 각 프레임에 대한 특징점의 추적은 Lucas-Kanade 방법을 사용하였다. 3D 좌표 추정 방법으로 개선된 직교분해기법을 사용하였다. 개선된 직교분해기법에서는 3D 좌표를 복원함과 동시에 카메라의 위치와 방향을 계산할 수 있다. 복원된 부분 데이터들은 전체를 이루는 일부분이므로, 융합을 통해 완성된 모습을 만들 수 있다. 복원된 부분 데이터들의 서로 다른 좌표계를 기준 좌표계로 변환함으로써 융합할 수 있다. 융합은 카메라의 모션에 해당하는 카메라의 위치와 방향에 의존된다. 융합 과정은 모두 선형으로 평균 0.5초 이하의 수행 속도를 보이며 융합의 오차는 평균 0.1cm 이하의 오차를 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.669-672
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• 2003

3D object recognition is difficult but important in computer vision. The important thing is to understand about the relationship between a geometric structure in three dimensions and its image projection. Most 3D recognition systems construct models either manually or by training the pose and orientation of the objects. But both approaches are not satisfactory. In this paper, we focus on a commercial CAD model as a third type of model building for vision. The models are expressed in Initial Graphics Exchanges Specification(IGES) output and reconstructed in a pinhole camera coordinate.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.215-218
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• 2014

High combustion efficiency of hydrogen could make it an ideal source of green energy in the future. At this time, high pressure vessel is the most reasonable method of storing hydrogen. However, such a high pressurized vessel could pose a critical threat if ruptured. For this reason, it is important to understand the mechanism of hydrogen's self-ignition when a high-pressure hydrogen released into air. This paper presents several visualization images as experimental results using high-speed camera. From the visualization images, the ignition is initiated near rupture disk immediately after failure of disk. And the initial ignition and flame is stronger as a rupture pressure increases. However, this ignition region do not affect the general self-ignition mechanism when a high-pressure hydrogen is released into air through tue after failure of disk.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.183-188
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• 2009

In this paper, we preset a method for the development of u-GIS outdoor augmented reality(AR) system. The proposed system is consist of three parts. First, sensor acquisition and calibration for AR, Second, camera and sensor based tracking for AR, Third, integration of sensor information and 3D models. We combine spatial information of real and virtual spaces through u-GIS AR system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.164-170
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• 2011

This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) method using both position and orientation information of ceiling lamps. Conventional approaches used corner or line features as landmarks in their SLAM algorithms, but these methods were often unable to achieve stable navigation due to a lack of reliable visual features on the ceiling. Since lamp features are usually placed some distances from each other in indoor environments, they can be robustly detected and used as reliable landmarks. We used both the position and orientation of a lamp feature to accurately estimate the robot pose. Its orientation is obtained by calculating the principal axis from the pixel distribution of the lamp area. Both corner and lamp features are used as landmarks in the EKF (Extended Kalman Filter) to increase the stability of the SLAM process. Experimental results show that the proposed scheme works successfully in various indoor environments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.1-37
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• 2002

Localization is one of the most important functions for the mobile robot navigating in the unstructured environment. Most of previous localization schemes estimate current position and pose of mobile robot by applying various localization algorithms with the information obtained from sensors which are set on the mobile robot, or by recognizing an artificial landmark attached on the wall, or objects of the environment as natural landmark in the indoor environment. Several drawbacks about them have been brought up. To compensate the drawbacks, a new localization method that estimates the global position of the mobile robot by using a camera set on ceiling in the corridor is proposed. This sch...