• Journal of Internet Computing and Services
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• v.18 no.4
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• pp.61-67
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• 2017

Recently, CCTV has been combined with areas such as big data, artificial intelligence, and image analysis to detect various abnormal behaviors and to detect and analyze the overall situation of objects such as people. Image analysis research for this intelligent video surveillance function is progressing actively. However, CCTV images using 2D information generally have limitations such as object misrecognition due to lack of topological information. This problem can be solved by adding the depth information of the object created by using two cameras to the image. In this paper, we perform background modeling using Mixture of Gaussian technique and detect whether there are moving objects by segmenting the foreground from the modeled background. In order to perform the depth information-based segmentation using the RGB information-based segmentation results, stereo-based depth maps are generated using two cameras. Next, the RGB-based segmented region is set as a domain for extracting depth information, and depth-based segmentation is performed within the domain. In order to detect the center point of a robustly segmented object and to track the direction, the movement of the object is tracked by applying the CAMShift technique, which is the most basic object tracking method. From the experiments, we prove the efficiency of the proposed object detection and tracking method using the RGB-D model.

• Spatial Information Research
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• v.22 no.1
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• pp.65-73
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• 2014

Recently indoor navigation with indoor map such as Indoor Google Maps is served. For the services, constructing indoor data are required. CityGML and IFC are widely used as standards for representing indoor data. The data models contains spatial information for the indoor visualization and analysis, but indoor navigation requires semantic and topological information like graph as well as geometry. For this reason, IndoorGML, which is a GML3 application schema and data model for representation, storage and exchange of indoor geoinformation, is under standardization of OGC. IndoorGML can directly describe geometric property and refer elements in external documents. Because a lot of data in CityGML or IFC have been constructed, a huge amount of construction time and cost for IndoorGML data will be reduced if CityGML can help generate data in IndoorGML. Thus, this paper suggest practical use of CityGML including deriving from and link to CityGML. We analyze relationships between IndoorGML and CityGML. In this paper, issues and solutions for linkage of IndoorGML and CityGML are addressed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.69-74
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• 2015

To analyze quantitatively environmental characteristics of cultivation area of citrus, Satsuma mandarin (Citrus unshiu Marc.), we made digital maps of environmental elements such as topography and climate. Elevation, degree of slope, and slope aspect were selected as elements of topological environment, and the annual mean air temperature, annual total precipitation, mean air temperature on January, extreme value of daily minimum air temperature, and the number of days below $-5^{\circ}C$ were selected as elements of climatic environments. The grid values of 8 environmental elements were extracted by shape of citrus farm area and analyzed distribution patterns. We can determine 3 agroclimatic criteria for growing Satsuma mandarin as over $14.5^{\circ}C$ of annual mean air temperature, over $-10.0^{\circ}C$ of extreme value of daily minimum air temperature, and less 5 days of below $-5^{\circ}C$ of daily minimum air temperature.