• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.200-204
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• 2008

In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3E
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• pp.50-55
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• 1997

Based on the anthropometric data of Korea male adults, a head and torso simulator(HATS) is constructed to measure its head related transfer functions (HRTFs) which can be used for three dimensional (3-D) sound localization. The HRTFs binaural impulse responses, are measured in an anechoic chamber using a burst maximum length sequence (MLS) signal of 65,535 samples and 32,768 samples acquisition at the sampling rate of 75.47kHz. Also measured are the impulse responses of a driving loudspeaker and some headphones for sound reproduction to get the exact HRTF of the HATS-alone. Through a post-processing procedure, the impulse-version HRTFs at the sampling frequency of 44.1 kHz, which have filter lengths of 512 points, are finally obtained. As an application of the measured HRTFs, a 3-D sound processor for headphone reproduction has been developed. The signal intervals to be processed can be selected and each interval is manipulated to have its diretionality and distance information by using corresponding HRTF and energy control.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.312-320
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• 2020

3D scanning began in the field of manufacturing. In the construction field, a BIM (Building Information Modeling)-based 3D modeling environment was developed and used for the overall construction, such as factory prefabrication, structure construction inspection, plant facility, bridge, tunnel structure inspection using 3D scanning technology. LiDARs have higher accuracy and density than mobile scanners but require longer registration times and data processing. On the other hand, in interior building space management, relatively high accuracy is not needed, and the user can conveniently move with a mobile scan system. This study derives considerations for the development of Simultaneous Localization and Mapping (SLAM)-based Scan Backpack systems that move freely and support real-time point cloud registration. This paper proposes the mobile scan system, framework, and component structure to derive the considerations and improve scan productivity. Prototype development was carried out in two stages, SLAM and ScanBackpack, to derive the considerations and analyze the results.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.231-238
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• 2022

Mine detection has been mainly studied with images of the forward-looking sonar. Forward-looking sonar assumes the propagation path of the sound wave as a straight path, creating the surrounding images. This might lead to errors in the detection by ignoring the refraction of the sound wave. In this study, we propose a mine localization method that can robustly identify the location of mines in an underwater environment by considering the refraction of sound waves. We propose a method of estimating the elevation angle of arrival of the target echo signal in a single receiver, and estimate the mine location by applying the estimated elevation angle of arrival to ray tracing. As a result of simulation, the method proposed in this paper was more effective in estimating the mine localization than the existing method that assumed the propagation path as a straight line.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.318-327
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• 2009

In this paper, we propose a 3-D geometric localization method for near-field broadband source in shallow water environments. According to the waveguide invariant theory, slope of the interference pattern which is seen in a sensor spectrogram directly proportional to a range of the source. The relative ratio of the range between source and sensors was estimated by matching of two interference patterns in spectrogram. Then this ratio is applied to the Apollonius's circle which shows the locus of a source whose range ratio from two sensors is constant. Two Apollonius's circles from three sensors make the intersection point that means the horizontal range and the azimuth angle of the source. And this intersection point is constant with source depth. Therefore the source depth can be estimated using 3-D hyperboloid equation whose range difference from two sensors is constant. To evaluate a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program and analysis of localization error is demonstrated. From simulation results, error estimate for range and depth is described within 50 m and 15 m respectively.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.557-565
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• 2009

To perceive the direction and the distance of a sound, we always use a couple of information. Head Related Transfer Function (HRTF) contains the information that sound arrives from a sound source to the ears of the listener, like differences of level, phase and frequency spectrum. For a reproduction system using 2 channels, we apply HRTF to many algorithms which make 3d sound. But it causes a problem to localize a sound source around a certain places which is called the cone-of-confusion. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization. The difference of frequency spectrum and psychoacoustics theory are used to boost the spectral cue among each directions. To confirm the performance of the algorithm, informal listening tests are carried out. As a result, we can make the improved 3d sound in 2 channel system based on a headphone. Also sound quality of improved 3d sound is much better than conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.30 no.4
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• pp.167-180
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• 2011

Recently, 3-D audio technologies are commonly implemented through headphones. A major problem of the headphone-based 3-D audio is in-the-head localization, which occurs due to the inaccurate Head-Related Transfer Function (HRTF). Since the individual measurements of HRTFs are impractical, there have been several researches for HRTF customization. In this paper, an efficient method of customizing HRTFs for the sound externalization is proposed. Firstly, it is determined which part will be customized in HRTF through psychoacoustical experiments. Then, the method controlling spectral notches and envelopes to provide individual localization cues are described. Since the proposed method is based on a critical-band rate, the structure is much simpler than that of previous studies, but still effective. The performance was evaluated through a series of subjective tests, and the results confirmed that the customized HRTF using proposed method could replace the measured individual HRTF successfully.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.81-86
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• 2019

Although the localization rate of shipbuilding and marine equipment goods is set to be 70 percent by 2020, but the localization rate of equipment and materials for shipbuilding and marine facilities is currently 10 to 30 percent. For Korea's Big 3 shipbuilders, which build 70 percent of the world's largest shipbuilders, localization of shipbuilding equipment and equipment is an essential factor. In particular, there is a growing need to localize equipment and materials in terms of the number of lead standards and A/S. It is expected that there will be a rapid expansion of LNG carriers in the future, and it is necessary to develop equipment and equipment materials of LNG ships. In this study, the design and manufacture of LNG vessel equipment was conducted. Design and basic performance tests of 4-inch QCDC for LNG bunkering were conducted.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.