• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.10
• /
• pp.6917-6924
• /
• 2015

The universal nature of humans is formed by the view angle and the visibility range. However, the majority of theories on spatial structure analysis based on the visual perception do neither reflect the view angle nor consider only the flat view angle. Some theories that reflect them is a theory where the part included in the view angle and the part excluded in the view angle have been separated in a dichotomous way, excluding the universal characteristics of humans. This study applied an observing probability to a 3-D visibility analysis theory by conducting a eye-tracking experiment, empirically determining the limits of the field of view, and deriving the observing probability by view angle. In addition, it attempted to identify the probability by manufacturing an application of spacial, visual perception analysis and applying the concept of multiple frustum culling. For the characteristics of observation, the data were measured and collected regarding the walking course for 3 minutes for an optional space, aimed for 33 people as subjects. Subsequently, the data were prepared by analyzing the observation fixation frequency probability.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.2
• /
• pp.121-132
• /
• 2016

This study proposes an approach for simulating high spatial resolution satellite images acquired under arbitrary sun-sensor geometry using existing images and 3D (three-dimensional) data. First, satellite images, having significant differences in spectral regions compared with those in the simulated image were transformed to the same spectral regions as those in simulated image by using the UPDM (Universal Pattern Decomposition Method). Simultaneously, shadows cast by buildings or high features under the new sun position were modeled. Then, pixels that changed from shadow into non-shadow areas and vice versa were simulated on the basis of existing images. Finally, buildings that were viewed under the new sensor position were modeled on the basis of open library-based 3D reconstruction program. An experiment was conducted to simulate WV-3 (WorldView-3) images acquired under two different sun-sensor geometries based on a Pleiades 1A image, an additional WV-3 image, a Landsat image, and 3D building models. The results show that the shapes of the buildings were modeled effectively, although some problems were noted in the simulation of pixels changing from shadows cast by buildings into non-shadow. Additionally, the mean reflectance of the simulated image was quite similar to that of actual images in vegetation and water areas. However, significant gaps between the mean reflectance of simulated and actual images in soil and road areas were noted, which could be attributed to differences in the moisture content.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.31 no.4
• /
• pp.207-213
• /
• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

• The KIPS Transactions:PartD
• /
• v.15D no.5
• /
• pp.609-620
• /
• 2008

The service handling the map data in the mobile device including navigation, LBS, Telematics, and etc., becomes various. The size of map data which is stored and managed in the mobile device is growing and reaches in several GB. The conventional navigation system has used the read-only PSF (physical storage format) in order to enhance the performance of system by maximum in the mobile device which has limited resources. So though a little part of the map data is changed the whole data must be updated. In general, it takes several ten minutes to write the 2 GB map data to a flash memory of mobile device. Therefore, we have developed the mobile spatial DBMS (database management system) to solve the problem which is that the partial map data couldn't be updated in the conventional navigation system. And we suggest the policy to guarantee the performance of the navigation system which is implemented using the spatial mobile DBMS and verify this by experiment.

• Journal of Cadastre & Land InformatiX
• /
• v.48 no.2
• /
• pp.213-225
• /
• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• 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%.

• Journal of Industrial Convergence
• /
• v.20 no.7
• /
• pp.57-64
• /
• 2022

There are various structures in the underground space, and the structures is managed as 3D data in Integrated Underground Geospatial Map Management System(IUGMMS). The worker transmits and updates the integrated map including the changed underground geospatial data to IUGMMS with the completed book submission program. However, there is a problem in that the transmission time and the update time is delayed because the size of the integrated map file is large. In this paper, we try to extract and transmit only the changed integrated map by obtaining and comparing each spatial characteristic information of the integrated map. As a result of the experiment, the transmission time of the suggestion method is short and the update time is also short than the transitional method because the suggestion method transmits only the integrated map including the changed underground geospatial data. As a result, it was possible to reduce the delay time in transmitting and updating the changed integrated map.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.5
• /
• pp.247-255
• /
• 2023

In order to create a virtual reality space in the metaverse, accurate tracking sensors and implementation are required. Most government agencies and corporations performs tracking to use their own tracking sensors and a base stations, such as VIVE. The VIVE method may have tracking problems due to spatial constraints and obstacles or nearby structures, and it is also that the number of people that can be accommodated within the space is also limited. In this paper, we designed and implemented metaverse using an IR sensor tracking system to freely track the spatial virtual reality metaverse, and we experimented contents in metaverse by placing IR sensors additionally on the floor and ceiling if needed in order to flexibly configure the metaverse space. As a result of the experiment, the tracking stability of the IR-tracking system was approximately 12% higher than the VIVE method. Additionally, adding more tracking sensors on the floor increases tracking stability and allows for a stable representation of virtual space.

• Journal of Korean Physical Therapy Science
• /
• v.11 no.2
• /
• pp.27-37
• /
• 2004

The propose of the study was to evaluate the efficacy of the partial body weight support during treadmill training on the ambulation in elderly with chronic stroke. Fourteen hemiplegic volunteers participated and were divided into an experimental and control groups. In the experimental group, the body weight support during treadmill training was performed 3 times per week for 6 weeks. In the control group, usual treadmill training was applied. Before and after experiments, temporal-spatial gait parameters were measured. The date of 14 patients who carried out the whole experimental course were statistically analyzed. The results of the study were : 1. In the comparison of gait velocity before and after experiment, the gait velocity was significantly increased in the experimental group and the control group(p<.05). In the comparison of difference of the gait velocity between groups, there was not significant difference between the experimental group and the control group(p>.05). 2. In comparison of gait cadence before and after experiment, the gait cadence was significantly increased in both groups(p<.05). In the comparison of difference of the gait cadence between groups, there was not significant difference between the experimental group and the control group(p>.05). 3. In the comparison of step length before and after experiment, the step length was significantly increased in the experimental group and the control group(p<.05). In the comparison of difference of the step length between groups, there was not significant difference between the experimental group and the control group(p>.05). 4. In the comparison of vastus medialis root mean square(RMS) before and after experiment, the vastus medialis RMS was significantly increased in the experimental group(p<.05). In the comparison of vastus medialis root mean square(RMS) before and after experiment, the vastus medialis RMS was not significantly increased in the experimental group(p>.05). In the comparison of difference of the vastus medialis RMS between groups, there was not significant difference between the experimental group and the control group(p>.05). 5. In the comparison of latency of somatosensory evoke potential(SSEP) before and after experiment, the latency of SSEP was significantly increased in the experimental group(p<.05). In the comparison of latency of somatosensory evoke potential(SSEP) before and after experiment, the latency of SSEP was significantly decreased in the control group(p>.05). In the comparison of difference of the latency of SSEP between groups, there was not significant difference between the experimental group and the control group(p>.05). 6. In the comparison of functional ambulation profile(FAP) before and after experiment, the FAP was not significant difference in the experimental group and the control group(p>.05). In the comparison of difference of the FAP between groups, there was not significant difference between the experimental group and the control group(p>.05).

• Korean Journal of Remote Sensing
• /
• v.28 no.4
• /
• pp.357-367
• /
• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.