• Title/Summary/Keyword: Spatial Mapping

Search Result 884, Processing Time 0.031 seconds

Temporal and Spatial Object Grouping for Distributed Multimedia Streaming (분산 멀티미디어 스트리밍을 위한 시/공간적 객체 그룹화)

  • Lee, Chong-Deuk
    • Journal of the Korea Computer Industry Society
    • /
    • v.8 no.2
    • /
    • pp.113-122
    • /
    • 2007
  • Recently, there are many research interests in providing efficient, temporal and spatial distribution multimedia streaming service. This paper proposed a temporal and spatial object grouping method for distribution multimedia streaming service. The proposed method performs the grouping structure by filtering and mapping with the collected frame object in application domains and it's peformed by JM relationship with the mapped frame objects. The results show that the performance provides the better than the other methods.

  • PDF

Media GIS Web Service Architecture using Three-Dimensional GIS Database

  • Kim, Sung-Soo;Kim, Kyong-Ho;Kim, Kyung-Ok
    • Proceedings of the KSRS Conference
    • /
    • 2002.10a
    • /
    • pp.117-122
    • /
    • 2002
  • In this paper, we propose Media GIS web service architecture using 3D geographical database and GPS-related data resulted from 4S-Van. We introduce a novel interoperable geographical data service concept; so-called, Virtual World Mapping (VWM) that can map 3D graphic world with real-world video. Our proposed method can easily retrieve geographical in-formation and attributes to reconstruct 3D virtual space according to certain frame in video sequences. Our proposed system architecture also has an advantage that can provide geographical information service with video stream without any image processing procedures. In addition to, describing the details of our components, we present a Media GIS web service system by using GeoVideo Server, which performs VWM technique.

  • PDF

An Evaluation Scheme on Feasibility in Public Sector for 3D Geo-Spatial Information - Focusing on Production of Digital Mapping (3차원 공간정보의 공공부문 사업성 평가 방안 - 2차원 수치지도 제작 업무를 대상으로)

  • Joo, Yong Jin;Kim, Kang Soo;Hahm, Chang Hahk
    • Journal of Korean Society for Geospatial Information Science
    • /
    • v.20 no.3
    • /
    • pp.73-82
    • /
    • 2012
  • In order to carry out efficient investment and successful business in national geo-spatial industry, economic assessment on the field of 3D geo-information has recently emerged as a serious issue. Therefore, this study is intended to offer cost-effective evaluation scheme which are proper for 3D geo-spatial information, especially focusing on development of orthophoto and DEM. The study is organized as follows. The first section clarifies preliminary rules for feasibility by defining target work and category in order to estimate benefit. Then, this paper will be limited to consideration of production of digital mapping for target business which is expected to create high value and its benefit from cost reduction is suggested. Drawing from the AHP(Analytic Hierarchy Process) methods, this study comprehensively described final result and implication to examine business value. Consequently, this study can suggest economical evaluation methods on 3D geo-spatial information industry, which takes up a considerable part of immaterial benefit and has difficulties in economic assessment and estimation. preventing a variety of errors in system operation in advance.

Salient Object Detection Based on Regional Contrast and Relative Spatial Compactness

  • Xu, Dan;Tang, Zhenmin;Xu, Wei
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.7 no.11
    • /
    • pp.2737-2753
    • /
    • 2013
  • In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

How Language Locates Events

  • 남승호
    • Korean Journal of Cognitive Science
    • /
    • v.10 no.1
    • /
    • pp.45-55
    • /
    • 1999
  • This paper argues that the basic modes of spatial cognition can be best identified in terms of argument/participant location, and shows that natural language uses‘simple’types of semantic denotations to encode spatial cognition, and further notes that spatial expressions should be interpreted not as locating an event/state as a whole but as locating arguments/participants of the event. The ways of locating events/states are identified in terms of argument orientation(AO), Which indicates semantic patterns of linkiarticipant location. and shows that natural langrage uses ng locatives to specific arguments. Four patterns of argument orientation described here reveal substantial modes of spatial cognition. and the AO patterns are mostly determined by the semantic classes of English verbs combining with locative expressions, i.e., by the event type of the predicate. As for the denotational constraint of locatives, the paper concludes that semantic denotations of locative PPs are restricted to the intersecting functions mapping relations to relations.

  • PDF

Spatial Prediction of Soil Carbon Using Terrain Analysis in a Steep Mountainous Area and the Associated Uncertainties (지형분석을 이용한 산지토양 탄소의 분포 예측과 불확실성)

  • Jeong, Gwanyong
    • Journal of The Geomorphological Association of Korea
    • /
    • v.23 no.3
    • /
    • pp.67-78
    • /
    • 2016
  • Soil carbon(C) is an essential property for characterizing soil quality. Understanding spatial patterns of soil C is particularly limited for mountain areas. This study aims to predict the spatial pattern of soil C using terrain analysis in a steep mountainous area. Specifically, model performances and prediction uncertainties were investigated based on the number of resampling repetitions. Further, important predictors for soil C were also identified. Finally, the spatial distribution of uncertainty was analyzed. A total of 91 soil samples were collected via conditioned latin hypercube sampling and a digital soil C map was developed using support vector regression which is one of the powerful machine learning methods. Results showed that there were no distinct differences of model performances depending on the number of repetitions except for 10-fold cross validation. For soil C, elevation and surface curvature were selected as important predictors by recursive feature elimination. Soil C showed higher values in higher elevation and concave slopes. The spatial pattern of soil C might possibly reflect lateral movement of water and materials along the surface configuration of the study area. The higher values of uncertainty in higher elevation and concave slopes might be related to geomorphological characteristics of the research area and the sampling design. This study is believed to provide a better understanding of the relationship between geomorphology and soil C in the mountainous ecosystem.

[Retracted]Hot Spot Analysis of Tourist Attractions Based on Stay Point Spatial Clustering

  • Liao, Yifan
    • Journal of Information Processing Systems
    • /
    • v.16 no.4
    • /
    • pp.750-759
    • /
    • 2020
  • The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

A complete 3D map of Bell Glasstone spatial correction factors for BRAHMMA subcritical core

  • Shukla, Shefali;Roy, Tushar;Kashyap, Yogesh;Shukla, Mayank;Singh, Prashant
    • Nuclear Engineering and Technology
    • /
    • v.54 no.9
    • /
    • pp.3488-3493
    • /
    • 2022
  • Accelerator driven subcritical systems have long been discussed as facilities which can be used for solving the nuclear waste problem. The physics of these systems is very different from conventional reactors and new techniques had to be developed for reactivity monitoring. One such technique is the Area Ratio Method which studies the response of a subcritical system upon insertion of a large number of neutron pulses. An issue associated with this technique is the spatial dependence of measured reactivity which is intrinsic to the sub criticality of the system since the reactor does not operate on the fundamental mode and measured reactivity depends on the detector position. This is generally addressed by defining Bell-Glasstone spatial correction factor. This factor upon multiplication with measured reactivity gives the correct reactivity which is independent of detector location. Monte Carlo Methods are used for evaluating these factors. This paper presents a complete three dimensional map of spatial correction factors for BRAHMMA subcritical system. In addition, the dataset obtained also helps in identifying detector locations where the correction factor is close to unity, thereby implying no correction if the detector is used at those locations.

Time-series Mapping and Uncertainty Modeling of Environmental Variables: A Case Study of PM10 Concentration Mapping (시계열 환경변수 분포도 작성 및 불확실성 모델링: 미세먼지(PM10) 농도 분포도 작성 사례연구)

  • Park, No-Wook
    • Journal of the Korean earth science society
    • /
    • v.32 no.3
    • /
    • pp.249-264
    • /
    • 2011
  • A multi-Gaussian kriging approach extended to space-time domain is presented for uncertainty modeling as well as time-series mapping of environmental variables. Within a multi-Gaussian framework, normal score transformed environmental variables are first decomposed into deterministic trend and stochastic residual components. After local temporal trend models are constructed, the parameters of the models are estimated and interpolated in space. Space-time correlation structures of stationary residual components are quantified using a product-sum space-time variogram model. The ccdf is modeled at all grid locations using this space-time variogram model and space-time kriging. Finally, e-type estimates and conditional variances are computed from the ccdf models for spatial mapping and uncertainty analysis, respectively. The proposed approach is illustrated through a case of time-series Particulate Matter 10 ($PM_{10}$) concentration mapping in Incheon Metropolitan city using monthly $PM_{10}$ concentrations at 13 stations for 3 years. It is shown that the proposed approach would generate reliable time-series $PM_{10}$ concentration maps with less mean bias and better prediction capability, compared to conventional spatial-only ordinary kriging. It is also demonstrated that the conditional variances and the probability exceeding a certain thresholding value would be useful information sources for interpretation.

Area-to-Area Poisson Kriging and Spatial Bayesian Analysis in Mapping of Gastric Cancer Incidence in Iran

  • Asmarian, Naeimehossadat;Jafari-Koshki, Tohid;Soleimani, Ali;Ayatollahi, Seyyed Mohammad Taghi
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.17 no.10
    • /
    • pp.4587-4590
    • /
    • 2016
  • Background: In many countries gastric cancer has the highest incidence among the gastrointestinal cancers and is the second most common cancer in Iran. The aim of this study was to identify and map high risk gastric cancer regions at the county-level in Iran. Methods: In this study we analyzed gastric cancer data for Iran in the years 2003-2010. Area-to-area Poisson kriging and Besag, York and Mollie (BYM) spatial models were applied to smoothing the standardized incidence ratios of gastric cancer for the 373 counties surveyed in this study. The two methods were compared in term of accuracy and precision in identifying high risk regions. Result: The highest smoothed standardized incidence rate (SIR) according to area-to-area Poisson kriging was in Meshkinshahr county in Ardabil province in north-western Iran (2.4,SD=0.05), while the highest smoothed standardized incidence rate (SIR) according to the BYM model was in Ardabil, the capital of that province (2.9,SD=0.09). Conclusion: Both methods of mapping, ATA Poisson kriging and BYM, showed the gastric cancer incidence rate to be highest in north and north-west Iran. However, area-to-area Poisson kriging was more precise than the BYM model and required less smoothing. According to the results obtained, preventive measures and treatment programs should be focused on particular counties of Iran.