• The KIPS Transactions:PartD
• /
• v.9D no.1
• /
• pp.43-56
• /
• 2002

Most of works have been performed on representation of spatiotemporal objects from various points of view. Most of them represent spatiotemporal objects using approaches from GIS, temporal databases, object-oriented databases or data type. Spatiotemporal objects can be classified as objects whose position and shape changes discretely over time, objects whose position changes continuously and objects whose shape changes continuously as well as position. Previous works on spatiotemporal model have focused on only one of them. In this paper, we propose a spatiotemporal model that can represent three types of objects in Euclidean plan. For this purpose, we represent both discrete and continuous moving objects by defining temporal model extended from valid time and by defining relationship between two consecutive versions of objects. The proposed spatiotemporal object model is based on open GIS specification so that it has compatibility with existing spatial data model.

• Journal of Cadastre & Land InformatiX
• /
• v.44 no.2
• /
• pp.91-101
• /
• 2014

This study tried to create 3D object with LOD3 level for Korean traditional house which is atypical structure, upload to spatial information open platform and confirm the possibility for creating 3D-map. And this study tried to create 3D model for Korean traditional house based on BIM, performed 3D modeling for interior spatial information of Korean traditional house and confirm the development possibility of 3D modeling and visualization method of Korean traditional house. Also this study present the possibility of LOD4 level visualization for spatial information of Korean traditional house which is atypical structure, but 3D object with LOD4 level can't be uploaded to Spatial Information Open Platform currently, cause by data volume limitation of spatial information open platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.11a
• /
• pp.454-457
• /
• 1999

Most of oceanic information are related with spatial properties directly or impliedly and Presented differently depend on applications. So, without efficient integrated data model and strategies it inevitably occurs redundant development results of database itself and application systems. Therefor to avoid these inefficiencies it is most basic need to establish the ocean data infrastructure based on unified data model. In this paper we suggest the guideline for object data model based on ocean GIS concept followed with a sample primitive object data model implementing tile proposed guideline. With this unified data model we could expect the improvement ill the every phase of ocean related environment from data acquisition through translation and utilizing to service and exchange.

• Journal of KIISE:Databases
• /
• v.29 no.2
• /
• pp.110-118
• /
• 2002

This paper presents a 3-D graphic database system based on XML that supports content-based retrievals of 3-D images, Most of graphics application systems are currently centered around the processing of 2-D images and research works on 3-D graphics are mainly concerned about the visualization aspects of 3-D image. They do not support the semantic modeling of 3-D objects and their spatial relations. In our data model, 3-D images are represented as compositions of 3-D graphic objects with associated spatial relations. Complex 3-D objects are mode]ed using a set of primitive 3-D objects rather than the lines and polygons that are found in traditional graphic systems. This model supports content-based retrievals of scenes containing a particular object or those satisfying certain spatial relations among the objects contained in them. 3-D images are stored in the database as XML documents using 3DGML DTD that are developed for modeling 3-D graphic data. Finally, this paper describes some examples of query executed in our Web-based prototype database system.

• Journal of Korea Multimedia Society
• /
• v.11 no.6
• /
• pp.755-763
• /
• 2008

Silhouette is useful in computer graphics for a number of techniques such as non-photorealistic rendering, silhouette clipping, and blueprint generating. Methods for generating silhouette are classified into three categories: image-based, object-based, and hybrid-based. Hybrid-based method is effective in terms of time complexity but spatial coherence problem still remains. In this paper, we proposed a new hybrid-based method which produces 3D data for silhouette and also guarantees no spatial coherence problem. To verify the efficiency of the proposed algorithm, several experiments are conducted for various 3D models from simple to quite complex. Results show that our algorithm generates no gap between any two consecutive silhouette lines when the silhouette model is magnified significantly.

• Journal of Korea Spatial Information System Society
• /
• v.10 no.4
• /
• pp.59-66
• /
• 2008

GeoSensor network means sensor network infra and related software of specific form monitoring a variety of circumstances over geospatial. And these GeoSensor network is implemented by mixing data stream with spatial attribute, spatial relation. But, until a recent date sensor network system has been concentrated on a store and search method of sensor data stream except for a spatial information. In this paper, we propose a definition of spatial data stream and its join strategy model at GeoSensor network, which combine data stream with spatial data. Spatial data stream s defining in this paper are dynamic spatial data stream of a moving object type and static spatial data stream of a fixed type. Dynamic spatial data stream is data stream transmitted by moving sensor as GPS, while static spatial data stream is generated by joining a data stream of general sensor and a relation with location values of these sensors. This paper propose joins of dynamic spatial data stream and static spatial data stream, and cost models estimating join cost. Finally, we show verification of proposed cost models and performance by join strategy.

• Journal of Navigation and Port Research
• /
• v.36 no.7
• /
• pp.553-559
• /
• 2012

It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Erdos as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Erdos and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1141-1147
• /
• 2020

The hornet species are so similar in shape that they are difficult for non-experts to classify, and because the size of the objects is small and move fast, it is more difficult to detect and classify the species in real time. In this paper, we developed a system that classifies hornets species in real time based on a deep learning algorithm using a boundary box. In order to minimize the background area included in the bounding box when labeling the training image, we propose a method of selecting only the head and body of the hornet. It also experimentally compares existing boundary box-based object recognition algorithms to find the best algorithms that can detect wasps in real time and classify their species. As a result of the experiment, when the mish function was applied as the activation function of the convolution layer and the hornet images were tested using the YOLOv4 model with the Spatial Attention Module (SAM) applied before the object detection block, the average precision was 97.89% and the average recall was 98.69%.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.909-919
• /
• 2023

Benthic marine invertebrates, the invertebrates living on the bottom of the ocean, are an essential component of the marine ecosystem, but excessive reproduction of invertebrate grazers or pirate creatures can cause damage to the coastal fishery ecosystem. In this study, we compared and evaluated You Only Look Once Version 7 (YOLOv7), the most widely used deep learning model for real-time object detection, and detection tansformer (DETR), a transformer-based model, using underwater images for benthic marine invertebratesin the coasts of South Korea. YOLOv7 showed a mean average precision at 0.5 (mAP@0.5) of 0.899, and DETR showed an mAP@0.5 of 0.862, which implies that YOLOv7 is more appropriate for object detection of various sizes. This is because YOLOv7 generates the bounding boxes at multiple scales that can help detect small objects. Both models had a processing speed of more than 30 frames persecond (FPS),so it is expected that real-time object detection from the images provided by divers and underwater drones will be possible. The proposed method can be used to prevent and restore damage to coastal fisheries ecosystems, such as rescuing invertebrate grazers and creating sea forests to prevent ocean desertification.

• Korean Journal of Remote Sensing
• /
• v.27 no.4
• /
• pp.421-433
• /
• 2011

The importance of acquisition of road information has recently been increased with a rapid growth of spatial-related services such as urban information system and location based service. This paper proposes an automatic road extraction method using object-based approach which was issued alternative of pixel-based method recently. Firstly, the spatial objects were created by MSRS(Modified Seeded Region Growing) method, and then the key road objects were extracted by using properties of objects such as their shape feature information and adjacency. The omitted road objects were also traced considering spatial correlation between extracted road and their neighboring objects. In the end, the final road region was extracted by connecting discontinuous road sections and improving road surfaces through their geometric properties. To assess the proposed method, quantitative analysis was carried out. From the experiments, the proposed method generally showed high road detection accuracy and had a great potential for the road extraction from high resolution satellite images.