• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.585-597
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• 2009

This research aims to develop a registration method to remove the geometric inconsistency between aerial images and LIDAR data acquired from an airborne multi-sensor system. The proposed method mainly includes registration primitives extraction, correspondence establishment, and EOP(Exterior Orientation Parameters) adjustment. As the registration primitives, we extracts planar patches and intersection edges from the LIDAR data and object points and linking edges from the aerial images. The extracted primitives are then categorized into horizontal and vertical ones; and their correspondences are established. These correspondent pairs are incorporated as stochastic constraints into the bundle block adjustment, which finally precisely adjusts the exterior orientation parameters of the images. According to the experimental results from the application of the proposed method to real data, we found that the attitude parameters of EOPs were meaningfully adjusted and the geometric inconsistency of the primitives used for the adjustment is reduced from 2 m to 2 cm before and after the registration. Hence, the results of this research can contribute to data fusion for the high quality 3D spatial information.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.76-81
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• 2024

Recently, agricultural methods are changing from experience-based agriculture to data-based agriculture. Changes in agricultural production due to the 4th Industrial Revolution are largely occurring in three areas: smart sensing and monitoring, smart analysis and planning, and smart control. In order to realize open-field smart agriculture, information on the physical and chemical properties of soil is essential. Conventional physicochemical measurements are conducted in a laboratory after collecting samples, which consumes a lot of cost, labor, and time, so they are quickly measured in the field. Measurement technology that can do this is urgently needed. In addition, a soil analysis system that can be carried and moved by the measurer and used in Korea's rice fields, fields, and facility houses is needed. To solve this problem, our goal is to develop and commercialize software that can collect soil samples and analyze the information. In this study, basic soil composition measurement was conducted using soil composition measurement sensors consisting of hardness measurement and electrode sensors. Through future research, we plan to develop a system that applies soil sampling using a CCD camera, ultrasonic sensor, and sampler. Therefore, we implemented a sensor and soil analysis UI that can measure and analyze the soil condition in real time, such as hardness measurement display using a load cell and moisture, PH, and EC measurement display using conductivity.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.915-922
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• 2006

Recently, the requirements of the embedded software are getting diverse as the diversity of embedded software application fields increases. The systematic development methods are issued to deal with the dependency between hardware and software. However, the existing development methods have not considered the software's close connection to hardware and the high-level reusability for common requirements of several similar domains. In this paper, we propose a design method of development process model of product lines to support an efficient development method for embedded software. For this, we firstly suggest a domain scoping method and an IDEF0(Integration DEFinition)-based business model for extracting the efficient requirements. Next, we present a component deriving method based on the service architecture and an architecture design method after considering the hardware dependency. And we explain the artifacts of MSDFS(Multi Sensor Data Fusion System) at each design step in order to show how the proposed model can be applied to the embedded software development.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.305-316
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• 2018

As the urbanization ratio increases, the heat environment in cities is becoming more important due to the urban heat island. In this study, the heat island spatial analysis was calculated and conducted for analysis of urban thermal environment of Sejong city, which was launched in 2012 and has been developed rapidly. To analyze the ratio and change rate of urban area, a multi temporal land cover map (2013 to 2015 and 2017) of study area is generated based on Landsat-8 OLI/TIRS (Operational Land Imager / Thermal Infrared Sensor) satellite imagery. Then, we select an TIR (Thermal Infrared) band from the two TIR bands provided by the Landsat-8, which is used for calculating the heat island potential, through the accuracy evaluation of the brightness temperature and AWS (Automatic Weathering Station) data. Based on the selected band and surface emissivity, land surface temperature is calculated and the estimated heat island potential change is analyzed. As a result, the land surface temperature of the high ratio and change rate of urban area was significantly higher than the surrounding area around $3^{\circ}C$ to $4^{\circ}C$, and the heat island potential was also higher around $4^{\circ}C$ to $5^{\circ}C$. However, the heat island phenomenon was alleviated in urban areas with high rate of change that also show high green area ratio. Therefore, we demonstrated that dense urban area increases the possibility of inducing heat island, but it can mitigate the heat island through green areas.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.535-544
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• 2016

Even though existing methods for orthophoto production using expensive aircraft are effective in large areas, they are drawbacks when dealing with renew quickly according to geographic features. But, as UAV(Unmanned Aerial Vehicle) technology has advanced rapidly, and also by loading sensors such as GPS and IMU, they are evaluates that these UAV and sensor technology can substitute expensive traditional aerial photogrammetry. Orthophoto production by using UAV has advantages that spatial information of small area can be updated quickly. But in the case of existing researches, images of same altitude are used in orthophoto generation, they are drawbacks about repetition of data and renewal of data. In this study, we targeted about small slope area, and by using low-end UAV, generated orthophoto and DEM(Digital Elevation Model) through different altitudinal images. The RMSE of the check points is σ_h = 0.023m on a horizontal plane and σ_v = 0.049m on a vertical plane. This maximum value and mean RMSE are in accordance with the working rule agreement for the aerial photogrammetry of the National Geographic Information Institute(NGII) on a 1/500 scale digital map. This paper suggests that generate orthophoto of high accuracy using a different altitude images. Reducing the repetition of data through images of different altitude and provide the informations about the spatial information quickly.