• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2447-2449
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• 2004

This paper presents the predicted polar mapping that is to improve the efficiency of an unexpected moving obstacle detecting system. When the movement of the robot per a step becomes a bit large then static objects or background are detected as moving objects. Thus, the velocity of the robot becomes so slow. Therefore, to enlarge the movement of the robot, we propose the predicted polar mapping that predicts the polar mapped image after robot moves to be admissible. In order to verify experimentally our proposed procedure, we make several comparative tests in the corridor.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Spatial Information Research
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• v.19 no.4
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• pp.73-79
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• 2011

With the recent increase in demand for geo-registered imagery, Mobile Mapping Systems(MMS), which can quickly construct geographic information, has become important. The main part of MMS is the high-precision observation system, which collects geographic information at a certain speed. MMS has a complex data generation process and requires a standard-specific vehicle for its use, limiting its application range. In this paper, lightweight MMS is proposed to overcome its complexity by replacing the time synchronizer with a high-speed camera and by stabilizing motion with MEMS IMU/GPS. The proposed low-cost, portable method is expected to produce of geo-registered imagery efficiently.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.55-60
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• 2011

The most basic algorithm in SLAM(Simultaneous Localization And Mapping) technique of mobile robots is EKF(Extended Kalman Filter) SLAM. However, it requires prior information of characteristics of the system and the noise model which cannot be estimated in accurate. By this limit, Kalman Filter shows the following behaviors in a highly uncertain environment: becomes too sensitive to internal parameters, mathematical consistency is not kept, or yields a wrong estimation result. In contrast, $H_{\infty}$ filter does not requires a prior information in detail. Thus, based on a idea that $H_{\infty}$ filter based SLAM will be more robust than the EKF-SLAM, we propose a framework of $H_{\infty}$ filter based SLAM and show that suggested algorithm shows slightly better result man me EKF-SLAM in a highly uncertain environment.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.223-230
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• 2020

Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

• Journal of information and communication convergence engineering
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• v.3 no.2
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• pp.80-83
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• 2005

At present, GML becomes the global standard for the XML encoding of geographic information and is the foundation for the Geo-Web. GML is being applied to a wide range of geographic applications including GIS and location-based services, telematics and intelligent transportation systems. In this paper, we propose the tourism information system for supporting the location based service application. We made an effort to design and implement a GIS computing environment by thin client for mobile web mapping service. We are interested in the GML applications that include traditional GIS system for navigation service and location finder for points of interest (POI) services. This paper summarizes the Tourism information system for location based service of a small area (Han-Ok Village with the Korean traditional houses in Jeonju-city), in which moving travelers can obtain proper information services at the current location associated with traditional monuments, cultural products, food, and conveniences. In the paper, we report on the design of the thin client/server system for a mobile environment. This paper is divided into three parts. First, we give a general overview of the organization of the system and of the important concerns of our design. Second we focus on our system supports for location and POI determination, and design concerns. Finally, we show the graphic user interface of PDA, the procedures involved in the service, and the executed results.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.301-306
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• 2016

This paper presents the results of a study for robust self-localization and indoor slam using external cameras (such as a CCTV) and odometry of mobile robot. First, a position of mobile robot was estimated by using maker and odometry. This data was then fused with camera data and odometry data using an extended kalman filter. Finally, indoor slam was realized by applying the proposed method. This was demonstrated in the actual experiment.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.129-134
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• 2003

Mobile Mapping System needs system calibration of multi sensors. System calibration is defined as determination of spatial and rotational offsets between the sensors. Especially, EO parameters of GPS/INS require knowledge of the calibration to camera frame. The calibration parameters must be determined with the highest achievable accuracy in order to get 3D coordinate points in stereo CCD images. This study applies Boresight calibration for the calibration between GPS/INS and camera, and estimates the Performance of the calibration.

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

• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.133-139
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• 2015

This paper surveys vision based autonomous navigation technologies for unmanned systems. Main branches of visual navigation technologies are visual servoing, visual odometry, and visual simultaneous localization and mapping (SLAM). Visual servoing provides velocity input which guides mobile system to desired pose. This input velocity is calculated from feature difference between desired image and acquired image. Visual odometry is the technology that estimates the relative pose between frames of consecutive image. This can improve the accuracy when compared with the exisiting dead-reckoning methods. Visual SLAM aims for constructing map of unknown environment and determining mobile system's location simultaneously, which is essential for operation of unmanned systems in unknown environments. The trend of visual navigation is grasped by examining foreign research cases related to visual navigation technology.