• Journal of the Korean Data and Information Science Society
• /
• v.19 no.3
• /
• pp.979-994
• /
• 2008

Moving objects are spatio-temporal data that change their location or shape continuously over time. Generally, if continuously moving objects are managed by a conventional database management system, the system cannot properly process the past and future location which is not stored in the database. Up to now, for the purpose of location tracking which is not stored, the linear interpolation to estimate the past location has been usually used. It is suitable for the moving objects on linear route, not curved route. In this paper, we propose a past location tracking algorithm for a moving object on curved routes, and also suggest a future location tracking algorithm using some past location information. We found that the proposed location tracking algorithm has higher accuracy than the linear interpolation function.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.340-342
• /
• 2003

Location based services based on positions of moving objects are expanding the business area gradually. The location is included all estimate position of the future as well as the position of the present and the past. Location based routing service is active business application in which the position information of moving objects is applied efficiently. This service includes the trajectory of past positions, the real-time tracing of present position of special moving objects, and the shortest and optimized paths combined with map information. In this paper, we describes the location based routing services is extend in distributed web GIS environment. Web GIS service systems provide the various GIS services of analyzing and displaying the spatial data with friendly user - interface. That is, we propose the efficient architecture and technologies for servicing the location based routing services in distributed web GIS environment. The position of moving objects is acquired by GPS (Global Positioning System) and converted the coordinate of real world by map matching with geometric information. We suppose the swapping method between main memory and storages to access the quite a number of moving objects. And, the result of location based routing services is wrapped the web-styled data format. We design the schema based on the GML. We design these services as components were developed in object-oriented computing environment, and provide the interoperability, language-independent, easy developing environment as well as re - usability.

• Journal of KIISE:Databases
• /
• v.34 no.4
• /
• pp.343-356
• /
• 2007

Due to advances in position monitoring technologies such as global positioning systems and sensor networks, recent position information of moving objects has the form of streaming data which are updated continuously and rapidly. In this paper we propose an efficient trajectory maintenance method that stores the streaming position data of moving objects in the limited size of storage space and estimates past positions based on the stored data. For this, we first propose a new concept of incremental extraction of position information. The incremental extraction means that, whenever a new position is added into the system, we incrementally re-compute the new version of past position data maintained in the system using the current version of past position data and the newly added position. Next, based on the incremental extraction, we present an overall framework that stores position information and estimates past positions in the stream environment. We then propose two polynomial-based methods, line-based and curve-based methods, as the method of estimating the past positions on the framework. We also propose three incremental extraction methods: equi-width, slope-based, and recent-emphasis extraction methods. Experimental results show that the proposed incremental extraction provides the relatively high accuracy (error rate is less than 3%) even though we maintain only a little portion (only 0.1%) of past position information. In particular, the curve-based incremental extraction provides very low error rate of 1.5% even storing 0.1% of total position data. These results indicate that our incremental extraction methods provide an efficient framework for storing the position information of moving objects and estimating the past positions in the stream environment.

• Journal of KIISE:Databases
• /
• v.33 no.3
• /
• pp.261-270
• /
• 2006

Positional data of moving objects can be regularly sampled in order to minimize the cost of data collection in LBS. Since position data which are regularly sampled cannot include the changes of position occurred between sampling periods, sampled position data differ from the data predicted by a time parameterized linear function. Uncertain position data caused by these differences make the accuracy of the range queries for present positions diminish in the TPR tree. In this paper, we propose the uncertainty region to handle the range queries for uncertain position data. The uncertainty region is defined by the position data predicted by the time parameterized linear function and the estimated uncertainty error. We also present the weighted recent uncertainty error policy and the kalman filter policy to estimate the uncertainty error. For performance test, the query processor based by the uncertainty region is implemented in the TPR tree. The experiments show that the Proposed query processing methods are more accurate than the existing method by 15%.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.2
• /
• pp.204-216
• /
• 2006

Latest advances in hardware technology and state of the art of mobile robot and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. And mobile service robot requires the perception of its present position to coexist with humans and support humans effectively in populated environments. To realize these abilities, robot needs to keep track of relevant changes in the environment. This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace) is used in order to achieve these goals. This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used to estimate the location of moving robot. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot. Its performance is verified by computer simulation and experiment.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.272-275
• /
• 2004

Recently, the services using position information of moving objects is embossed. Theses services needs the moving objects databases to manage moving object data with efficiency. To build the moving object databases, we must develop the moving object engine to mange, store, and search the spatio temporal data of moving object. The moving object engine has to support query syntax to search data that suitable for user need like LBS, Telematics, ITS, vehicle management system. In this paper, we design and implement the moving object engine to support service with moving object data. The moving object engine is able to support system environment that users are able to get the moving object data easily even they don't know complex data structure.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.64.5-64
• /
• 2001

It is a very important problem that we grasp the accurate position at car navigation system. The GPS has used for knowing position because of accumulating few errors, but it have errors that are Tropospheric error, ionospheric error and Multipath error and so on. In this paper, We estimate moving position of a vehicle by Kalman filter using initial value after deducing the line equation using initial value and target value of map data. Then, we compensate GPS errors compare estimated poing with GPS errors. The experimental results have shown that are compared position data during real travel with compensated position data which are got after applying the algorithm ...

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.7
• /
• pp.39-46
• /
• 2016

In this paper, we proposed an application which can conduct to take repetition images for special effect shooting at movies or drama using Bluetooth of smart device. The proposed application can move a camera with motors several times as the same moving after saving of the control data based on the application during specific time using Bluetooth. At the repetition moving, we do not permit to control motors of the camera by person for keeping the same start position and end position after saving the moving data. The camera motors are only moved remotely by saving data of the proposed application. We developed the proposed application and a hardware which works motors with camera to check performance evaluation. Then, we confirmed that the proposed application exactly did the same moving to the motors with camera several times according to saved data. Therefore, because the proposed application can take a same images as control remotely the motors of camera, it will be a useful technology for special effect shooting of movies or dramas.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.302-305
• /
• 2008

For an complete image composition to be stitched on several mosaic images, tracing displacement of direction and distance between successive images are important parameters. The input image is modeled by using a general second order two-dimensional Taylor-series and then converting it to a $3{\times}3$ correlation block and storing the data. A moving factor and coordinate is calculated by comparing the continuous correlation blocks. The experimentation result has a success rate of 85% for moving path tracing as continuous images are moved to 10% of image central position.

• International Journal of Precision Engineering and Manufacturing
• /
• v.5 no.1
• /
• pp.27-35
• /
• 2004

In the field of machine vision using a single camera mounted on a mobile robot, although the detection and tracking of moving objects from a moving observer, is complex and computationally demanding task. In this paper, we propose a new scheme for a mobile robot to track and capture a moving object using images of a camera. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.