• Journal of the Korea Safety Management & Science
• /
• v.4 no.1
• /
• pp.69-80
• /
• 2002

최근 컴퓨터 기술의 발전과 함께 Mobile 컴퓨터 환경도 함께 급속히 발전하고 있다. 이로 인해 오프라인 컴퓨팅 및 네트워킹을 이용하던 사용자들이 Mobile 컴퓨팅 환경을 자주 이용하게 되고, Mobile 솔루션에 대한 사용자의 요구도 다양화되고 있는 추세이다. 이 중 Mobile 지도 서비스는 휴대하기 편한 Pocket PC라고도 불리는 PDA(Personal Digital Assistants)는 자신의 현재 위치를 확인할 수 있는 GPS(Global Positioning System)가 급속도로 보급됨으로써 Mobile 환경에서 가장 활용도가 높은 서비스로 부각되고 있다. 가까운 미래의 IT기술은 GPS와 PDA 등을 연계한 e포지션의 폭발적인 이용 증대와 국내 원천기술에 의한 세계적인 사업모델의 탄생이 눈앞에 현실로 다가오고 있다는 점을 감안하면, GPS를 활용한 Mobile 기술력 확보는 국가적 차원에서 대단히 중요하다는 견지를 같이하는 전문가들이 많다. 이러한 시대적 요구 환경 하에서, 본 논문에서는 JAVA VM 기반의 무선위치추적 제어미들웨어와 GIS 프로그램(Vector MAP Viewer)을 구축함으로써 APTS의 효율성에 관한 연구를 제안하고, 앞으로의 향후 개선방향을 제시하고자 한다.

• Journal of Digital Contents Society
• /
• v.13 no.1
• /
• pp.31-36
• /
• 2012

Since the national standard topographic map is made by DXF format which is the results of the National Geographic Information System project and lots of CAD data and scanners can be used to acquire the data easily, the imports of existing DXF file will decrease the costs and time for data acquisition process. In addition, the spatial data such as topographic map should be able to convert to the middle file format such as PostScript in order to be exported into other systems. For this purpose, I design and implement three units of modules, which are File Manipulation Module, MVF Import Module, and MVF Export Module. Finally, I verify the actual transformation of topographic map that are DXF file format by conducting the series of tests.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1468-1471
• /
• 2005

This Paper is to find out a solution for the full-coverage algorithm requiring the real-time processing such as mobile home service robots and vacuum cleaner robots. Previous methods are used by adopting based grid approach method. They used lots of sensors, a high speed CPU, expensive ranger sensors and huge memory. Besides, most full-coverage algorithms should have a map before obstacle avoidance. However, if a robot able to recognize the tangent vector of obstacles, it is able to bring the same result with less sensors and simplified hardware. Therefore, this study suggests a topological based approach and a local obstacle voidance method using a few of PSD sensors and ultra sonic sensors. The simulation results are presented to prove its applicability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.5
• /
• pp.377-388
• /
• 2020

In this paper, the autonomous mobile robot whit only LRF sensors proposes an algorithm for avoiding moving obstacles in an environment where a global map containing fixed obstacles. First of all, in oder to avoid moving obstacles, moving obstacles are extracted using LRF distance sensor data and a global map. An ellipse-shaped safety radius is created using the sum of relative vector components between the extracted moving obstacles and of the autonomuos mobile robot. Considering the created safety radius, the autonomous mobile robot can avoid moving obstacles and reach the destination. To verify the proposed algorithm, use quantitative analysis methods to compare and analyze with existing algorithms. The analysis method compares the length and run time of the proposed algorithm with the length of the path of the existing algorithm based on the absence of a moving obstacle. The proposed algorithm can be avoided by taking into account the relative speed and direction of the moving obstacle, so both the route and the driving time show higher performance than the existing algorithm.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.352-354
• /
• 2007

This paper presents a method to estimate the position of a mobile robot by using a gyro sensor and accelerometer sensors on it. Together with contact sensors we propose a mapmaking algorithm for an indoor environment where the robot moves. The direction of robot can be estimated through a gyro sensor and the distance is founded out by accelerometers. Then one can presume the position of robot. Using the direction and distance values vector-based mapmaking job can be performed. Tactile sensors help the robot recognize the boundary limit value of indoor environment and decide outer wall line of the map.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2016.01a
• /
• pp.33-35
• /
• 2016

본 논문에서는 모바일 디바이스를 이용하여 촬영한 이미지 또는 이미 모바일 디바이스에 저장된 이미지를 사용자가 검색을 위한 질의어로 사용할 수 있는 방법에 대하여 제안한다. 기존의 모바일 검색엔진을 그대로 활용하기 위해 이미지 어노테이션에 기반한 태깅 키워드를 검색 이미지와 매칭하여 질의하는 방식으로 구현하며, 이 과정에서 이미지의 분석과 분류를 위한 SVM(Support Vector Machine)과 SIFT(Scale Invariant Feature Transform) 알고리즘을 사용하였으며, 이미지 어노테이션 태깅에 대한 키워드 매칭을 위해 빅데이터에서의 MapReduce를 응용하였다.

• Journal of Korea Multimedia Society
• /
• v.18 no.2
• /
• pp.233-243
• /
• 2015

A hotspot is a spatial pattern that properties or events of spaces are densely revealed in a particular area. Whereas location information is easily captured with increasing use of mobile devices, so is not our emotion unless asking directly through a survey. Tweet provides a good way of analyzing such spatial sentiment, but relevant research is hard to find. Therefore, we analyzed hotspots of emotion in the twitter using spatial autocorrelation. 10,142 tweets and related GPS data were extracted. Sentiment of tweets was classified into good or bad with a support vector machine algorithm. We used Moran's I and Getis-Ord $G_i^*$ for global and local spatial autocorrelation. Some hotspots were found significant and drawn on Seoul metropolitan area map. These results were found very similar to an earlier conducted official survey of happiness index.

• Journal of Digital Contents Society
• /
• v.12 no.1
• /
• pp.77-83
• /
• 2011

Providing services in a wireless environment with existing wired-based GIS solutions have many limitations such as slow communication, processing rates, and screen size. Among the components, data is considered to be the most important factor in GIS. In this paper, I describe MVF, the most recent technology pioneered by GIS researchers. MVF is a format for efficient usage of spatial object in order to express, save and transform in mobile GIS. First, I describe the definition of MVF syntax, then the implementation of Header Section Generation Module and Main Section Generation Module through the API. Since the issues of network traffic and Hangul processing in mobile GIS are important, I especially consider development of MVF in terms of spatial data size.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.535-544
• /
• 2018

Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. This study was conducted to segment and classify road objects using 3D point cloud data acquired by terrestrial mobile mapping system provided by National Geographic Information Institute. For this study, the original 3D point cloud data were pre-processed and a filtering technique was selected to separate the ground and non-ground points. In addition, the road objects corresponding to the lanes, the street lights, the safety fences were initially segmented, and then the objects were classified using the support vector machine which is a kind of machine learning. For the training data for supervised classification, only the geometric elements and the height information using the eigenvalues extracted from the road objects were used. The overall accuracy of the classification results was 87% and the kappa coefficient was 0.795. It is expected that classification accuracy will be increased if various classification items are added not only geometric elements for classifying road objects in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.5
• /
• pp.1690-1710
• /
• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.