• 대한기계학회논문집A
• /
• 제29권1호
• /
• pp.139-144
• /
• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• International Journal of Internet, Broadcasting and Communication
• /
• 제14권3호
• /
• pp.108-114
• /
• 2022

Autism (ASD) is a mental disorder characterized by a pronounced deficit in personal, social, speech, and other aspects of development and communication skills. Since autism is a complex developmental disorder that requires a lot of effort to recognize, this research was conducted to develop an interactive data Acquisition System and detect the first signs of ASD in children. The proposed system presents several variants of the tasks in an entertaining form, using hand tracking. Hand tracking is used to attract children's attention and interest them more to achieve more accurate results. The creation of the system is based on such libraries as OpenCV, PyGame, TensorFlow, and Mediapipe. The ultimate goal of the paper is to obtain data on the disease of autism in children for use in further diagnosis by medical experts.

• Journal of Information Processing Systems
• /
• 제18권3호
• /
• pp.359-373
• /
• 2022

The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

• 한국항공우주학회지
• /
• 제43권11호
• /
• pp.1016-1027
• /
• 2015

본 논문에서는 한국항공우주연구원에서 개발한 우주파편 충돌위험 종합관리 시스템(KARISMA, KARI Collision Risk Management System)의 궤도결정 성능에 대한 검증을 위해 저궤도 우주물체에 대한 레이더 관측데이터를 이용한 궤도결정을 수행하였다. 레이더 관측데이터로는 운영 종료된 우리별 3호(KITSAT-3)에 대해 독일 우주운영센터(GSOC, German Space Operations Center)의 협조로 얻은 TIRA(Tracking & Imaging Radar) 시스템의 실제 레이더 관측데이터를 사용하였다. 궤도결정 결과의 비교를 위해서 동일한 관측데이터에 대한 독일 우주운영센터의 정밀궤도결정 결과와 비교를 하였으며, 그 결과 약 60m 정도의 평균 위치오차가 있음을 확인할 수 있었다. 하지만 해당 결과는 관측데이터에 대한 오차보정 정보 등의 누락으로 인해 영향을 받았다. 이를 확인하기 위해 관측데이터에 대한 오차분석 및 관측오차가 큰 첫 관측데이터 아크를 배제하였다. 이 결과에서는 약 25m 정도의 평균 위치오차로 줄어듬을 확인할 수 있었다. 따라서 최종적으로 관측데이터에 대한 오차보정 정보를 적용할 경우 궤도결정 정밀도를 향상시킬 수 있을 것으로 기대된다.

• 한국정보통신학회논문지
• /
• 제13권11호
• /
• pp.2335-2340
• /
• 2009

본 논문은 레퍼런스(reference) 데이터 그룹을 효율적으로 생성하고 활용한 마커리스 증강현실(Markerless Augmented Reality)의 구현 방법을 제안한다. 카메라 설정과 레퍼런스 데이터 그룹 생성, 트래킹 (tracking) 부분으로 되어 있다. 효율적인 레퍼런스 데이터 그룹을 생성하기 위해서는 CAD모델과 같은 3D모델을 필요하며, 다양한 관점에서 본 레퍼런스 데이터 그룹을 생성해야 한다. 모델에 대한 영상에서 특징점들을 추출하고, 광선 추적법을 이용하여 그 특징점에 대응하는 3D좌표를 추출하여, 모델의 특징점들에 대한 2D/3D 대응접의 레퍼런스 데이터 그룹이 구성된다. 트래킹 할 때 현재 프레임영상에서 특징점 들이 가장 많이 매칭되는 레퍼런스 데이터와 그 주위의 모델 데이터만을 이용하기 때문에 빠르게 트래킹할 수 있다.

• 한국항공우주학회지
• /
• 제42권8호
• /
• pp.661-673
• /
• 2014

본 논문에서는 한국항공우주연구원에서 개발한 우주파편 충돌위험 종합관리 시스템(KARISMA, KARI Collision Risk Management System)의 궤도결정 기능을 이용하여, 정지궤도위성의 광학 관측데이터에 기반한 정밀궤도결정을 수행하였다. 광학 관측데이터로는 정지궤도 위성 ARTEMIS에 대한 유럽우주기구(ESA, European Space Agency)의 실제 광학 관측데이터를 사용하였다. 동일한 관측데이터에 대해 유럽우주기구의 정밀궤도결정 시스템을 통해 얻은 궤도결정 결과와 비교했을 때 약 420 m 정도의 평균 위치오차가 있음을 확인하였다. 또한, 4일간의 광학 관측데이터를 바탕으로 얻은 궤도결정 결과를 이용하여 궤도예측을 수행하였으며, 유럽우주기구의 궤도결정 결과와 비교했을 때 3일 동안 대략 500~600 m 수준의 위치오차를 보였다. 이러한 결과들에 기반하여 KARISMA의 궤도결정 성능이 우주파편 충돌위험 분석을 위해 사용가능한 수준임을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권6호
• /
• pp.2483-2503
• /
• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• 한국군사과학기술학회지
• /
• 제9권4호
• /
• pp.114-119
• /
• 2006

Data post-processing programs are used for analysis and visualization of the data obtained from computational fluid methods or flow field experiments. In this paper 3D data visualization system which combines a data visualization program with position tracking system using stereo cameras is introduced. This system offers virtual environment for visualization and analysis of three dimensional data.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
• /
• pp.353-356
• /
• 2005

In Taiwan, there are more the one hundred GPS tracking stations maintained by Ministry of the Interior (MOI), Academia Sinica, Central Weather Bureau and Central Geological Survey. In the further, they may be instead of the GPS controlling points after giving the lawful status. In other words, the engineers don't need to survey on the reference points when they are surveying in the field. They only need to download the GPS data via internet and process the observations in their company. The precise coordinates of the unknown points will be obtained. Therefore, the data qualities of the tracking stations are more and more important. In this study, six data quality indexes were adopted as follows: observations, cycle slips, multipath on L1, multipath on L2, clock offset and frequency stability. Besides, the relationships of the indexes and the positioning precision were found. The frequency stability of GPS receiver is the most important index, the cycle slip is the second index and the mutlipath is the third index. According to the results, the auto-analytical system of GPS data quality was established and the tracking stations were monitored. When the receiver got some problem or the station's environment changed, we hope to find and resolve the problems earlier to make sure the high data quality of the tracking stations. Moreover, we try to design a data quality verification to help users and let the engineers have more and more confidence when they use the data of GPS tracking stations.

• Journal of Information Processing Systems
• /
• 제19권1호
• /
• pp.80-88
• /
• 2023

RGB-thermal (RGB-T) tracking using unmanned aerial vehicles (UAVs) involves challenges with regards to the similarity of objects, occlusion, fast motion, and motion blur, among other issues. In this study, we propose dynamic tracking aggregation (DTA) as a unified framework to perform object detection and data association. The proposed approach obtains fused features based a transformer model and an L1-norm strategy. To link the current frame with recent information, a dynamically updated embedding called dynamic tracking identification (DTID) is used to model the iterative tracking process. For object association, we designed a long short-term tracking aggregation module for dynamic feature propagation to match spatial and temporal embeddings. DTA achieved a highly competitive performance in an experimental evaluation on public benchmark datasets.