• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.3-13
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• 2006

Extraction of man-made objects from high resolution satellite images has been studied by many researchers. In order to reconstruct accurate 3D building structures most of previous approaches assumed 3D information obtained by stereo analysis. For this, they need the process of sensor modeling, etc. We argue that a single image itself contains many clues of 3D information. The algorithm we propose projects virtual shadow on the image. When the shadow matches against the actual shadow, the height of a building can be determined. If the height of a building is determined, the algorithm draws vertical lines of sides of the building onto the building in the image. Then the roof boundary moves along vertical lines and the footprint of the building is extracted. The algorithm proposed can use the shadow cast onto the ground surface and onto facades of another building. This study compared the building heights determined by the algorithm proposed and those calculated by stereo analysis. As the results of verification, root mean square errors of building heights were about 1.5m.

• Journal of Sensor Science and Technology
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• v.12 no.2
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• pp.88-94
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• 2003

Electromyogram (EMG) is the bioelectric signal induced by motor nerves. Analyzing EMG with the movement produced by muscle contraction, we can provide input commands to a computer as a man-machine interface as well as can evaluate the patient's motional abnormality. In this paper, we developed an integrated miniaturized device which acquires and transmits the surface EMG of an interested muscle. Developed system measures $60{\times}40{\times}25mm$, weighs 100g. Using an amplifier circuitry on the electrodes and the radio frequency transmission, the developed system dispenses with the use of cables among the electrodes, amplifier, and the post processing system (personal computer). The wiring used in conventional systems can be obstacle for natural motion and source of motion artifacts. In results, the developed system improves not only the signal-to-noise ration in dynamic EMG measurement, but also the user convenience. We propose a new human-computer interface as well as a dynamic EMG measurement system as a possible application of the developed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.744-751
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• 2008

Ubiquitous computing is a new paradigm of telecommunication technology and is embedded with advanced computing technology to process a large amount of data in a normal environment. Generally, ail equipment is embedded with sensors and operating devices to interaction with communication functions. That is why ubiquitous computing must be able to access any devices anywhere at anytime in order to perform appropriate functions. Unfortunately, however, it is difficult to make an optimized design for applications which can effectively interaction with various functions in distributed environment like ubiquitous computing. Therefore, this paper is aimed at deploying interface with server nodules and virtual prototyping by utilizing LabVIEW and embedded application software with additional network function. In addition, given information about sensors collected from context-awareness and location-awareness, it will suggest the ideal ubiquitous application based on context-awareness and apply the advanced application to device control and monitoring through context awareness of lab.

• Journal of IKEEE
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• v.22 no.4
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• pp.970-977
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• 2018

The autonomous vehicle is based on an advanced driver assistance system (ADAS) consisting of a sensor that collects information about the surrounding environment and a control module that determines the measured data. As interest in autonomous navigation technology grows recently, an easy development framework for ADAS beginners and learners is needed. However, existing development and verification methods are based on high performance vehicle simulator, which has drawbacks such as complexity of verification method and high cost. Also, most of the schemes do not provide the sensing data required by the ADAS directly from the simulator, which limits verification reliability. In this paper, we present an interactive ADAS development and verification framework using a 3D vehicle simulator that overcomes the problems of existing methods. ADAS with image recognition based artificial intelligence was implemented as a virtual sensor in a 3D car simulator, and autonomous driving verification was performed in real scenarios.

• Smart Media Journal
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• v.11 no.9
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• pp.56-63
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• 2022

Recently, the frequency and range of algae occurrence in major rivers and lakes are increasing due to the increase in water temperature due to climate change, the inflow of excessive nutrients, and changes in the river environment. Abnormal algae include green algae and red algae. Green algae is a phenomenon in which blue-green algae such as chlorophyll (Chl-a) in the water grow excessively and the color of the water changes to dark green. In this study, a 3D virtual world of digital twin was built to monitor and control water quality information measured in ecological rivers and lakes in the living environment in real time from a remote location, and a sensor measuring device for water quality information based on the Internet of Things (IOT) sensor. We propose to build a smart water environment service platform that can provide algae warning and water quality forecasting by predicting the causes and spread patterns of water pollution such as algae based on AI machine learning-based collected data analysis.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.112-118
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• 2023

Internet of Things(IoT) technology is developing to a stage where the Internet and objects are connected and objects themselves analyze and judge data to interconnect the real world and the virtual world in real time. This technology consists of sensors, actuators, devices, and networks, and it is being applied in various fields. As the number of IoT devices and applications increases, data traffic also increases. In this paper, a messaging system is designed and implemented in order to analyze the performance between an IoT device and MQTT broker. The experimental was performed to measure MQTT-based round-trip time and message transmission time between the IoT device and the broker. The result shows that there is no packet loss, and propagation delay affects round-trip time.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.109-123
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• 2024

Research into vision-based end-to-end autonomous driving systems utilizing deep learning and reinforcement learning has been steadily increasing. These systems typically encode continuous and high-dimensional vehicle states, such as location, velocity, orientation, and sensor data, into latent features, which are then decoded into a vehicular control policy. The complexity of urban driving environments necessitates the use of state representation learning through networks like Variational Autoencoders (VAEs) or Convolutional Neural Networks (CNNs). This paper analyzes the impact of different image state encoding methods on reinforcement learning performance in autonomous driving. Experiments were conducted in the CARLA simulator using RGB images and semantically segmented images captured by the vehicle's front camera. These images were encoded using VAE and Vision Transformer (ViT) networks. The study examines how these networks influence the agents' learning outcomes and experimentally demonstrates the role of each state representation technique in enhancing the learning efficiency and decision- making capabilities of autonomous driving systems.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.902-909
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• 2015

In this paper, monovision based relative navigation for a satellite proximity operation is studied. The chaser satellite only uses one camera sensor to observe the target satellite and conducts image tracking to obtain the target pose information. However, by using only mono-vision, it is hard to get the depth information which is related to the relative distance to the target. In order to resolve the well-known difficulty in computing the depth information with the use of a single camera, the active contour method is adopted for the image tracking process. The active contour method provides the size of target image, which can be utilized to indirectly calculate the relative distance between the chaser and the target. 3D virtual reality is used in order to model the space environment where two satellites make relative motion and produce the virtual camera images. The unscented Kalman filter is used for the chaser satellite to estimate the relative position of the target in the process of glideslope approaching. Closed-loop simulations are conducted to analyze the performance of the relative navigation with the active contour method.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.62-67
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• 2009

Many interaction methods for augmented reality has attempted to reduce difficulties in tracking of interaction subjects by either allowing a limited set of three dimensional input or relying on auxiliary devices such as data gloves and paddles with fiducial markers. We propose Spatial Interaction (SPINT), a noncontact passive method that observes an occupancy state of the spaces around target virtual objects for interpreting user input. A depth-sensing camera is introduced for constructing the virtual space sensors, and then manipulating the augmented space for interaction. The proposed method does not require any wearable device for tracking user input, and allow versatile interaction types. The depth perception anomaly caused by an incorrect occlusion between real and virtual objects is also minimized for more precise interaction. The exhibits of dynamic contents such as Miniature AR System (MINARS) could benefit from this fluid 3D user interface.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.95-102
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• 2004

It is necessary to improve the exactness and adaptation of the working environment in the intelligent robot system. The vision sensor have been studied for this reason fur a long time. However, it is very difficult to perform the camera and robot calibrations because the three dimensional reconstruction and many processes are required for the real usages. This paper suggests the image based visual servoing to solve the problem of old calibration technique and supports OLP(Off-Line-Programming) path compensation. Virtual camera can be modeled from the real factors and virtual images obtained from virtual camera gives more easy perception process. Also, Initial path generated from OLP could be compensated by the pixel level acquired from the real and virtual, respectively. Consequently, the proposed visually assisted OLP teaching remove the calibration and reconstruction process in real working space. With a virtual simulation, the better performance is observed and the robot path error is calibrated by the image differences.