• Journal of Positioning, Navigation, and Timing
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• v.5 no.3
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• pp.137-144
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• 2016

In this paper, the performance of ranging measurement, which is generated using two receiver clock offsets in one receiver, was analyzed. A spoofer transmits a counterfeited spoofing signal which is similar to the GPS signal with hostile purposes, so the same tracking technique can be applied to the spoofing signal. The multi-correlator can generate two receiver clock offsets in one receiver. The difference between these two clock offsets consists of the path length from the spoofer to the receiver and the delay of spoofer system. Thus, in this paper, the ranging measurement was evaluated by the spoofer localization performance based on the time-of-arrival (TOA) technique. The results of simulation and real-world experiments show that the position and the system clock offset of the spoofer could be estimated successfully.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.154-159
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• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.30-39
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• 2004

This study aims at establishing a digital signal processing technique to control 3-D sound localization, especially focusing our ores on the role of information provided by Head-Related Transfer Function (HRTF). In order to clarify the cues to control the auditory distance perception, two conventional models named Hirsch-Tahara model and auditory parallax model were examined. As a result, it was shown that both models have limitations to universally explain the auditory distance perception. Hence, the auditory parallax model was extended so as to apply in broader cases of auditory distance perception. The results of the experiment by simulating HRTFs based on the extended parallax model showed that the cues provided by the new model were almost sufficient to control the perception of auditory distance from an actual sound source located within about 2m.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2044-2059
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• 2022

Recent works have shown that the geometric constraint can be harnessed to boost the performance of CNN-based camera localization. However, the existing strategies are limited to imposing image-level constraint between pose pairs, which is weak and coarse-gained. In this paper, we introduce a pixel-level epipolar geometry constraint to vanilla localization framework without the ground-truth 3D information. Dubbed EpiLoc, our method establishes the geometric relationship between pixels in different images by utilizing the epipolar geometry thus forcing the network to regress more accurate poses. We also propose a variant called EpiSingle to cope with non-sequential training images, which can construct the epipolar geometry constraint based on a single image in a self-supervised manner. Extensive experiments on the public indoor 7Scenes and outdoor RobotCar datasets show that the proposed pixel-level constraint is valuable, and helps our EpiLoc achieve state-of-the-art results in the end-to-end camera localization task.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.3
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• pp.452-458
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• 2013

Over the past several years, many studies have been carried out in the field of 3D data inspection systems. Several attempts have been made to improve the quality of manufactured parts. The introduction of laser sensors for inspection has made it possible to acquire data at a remarkably high speed. In this paper, a robust inspection technique for detecting defects in 3D pressed parts using laser-scanned data is proposed. Point cloud data are segmented for the extraction of features. These segmented features are used for shape matching during the localization process. An iterative closest point (ICP) algorithm is used for the localization of the scanned model and CAD model. To achieve a higher accuracy rate, the ICP algorithm is modified and then used for matching. To enhance the speed of the matching process, aKd-tree algorithm is used. Then, the deviation of the scanned points from the CAD model is computed.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.79.4-79
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• 2002

Our goal is the development of a system that estimates the location of interested point in a room with accuracy and low cost. Non-contacting position estimating method is widely used in various areas. Among these methods, acoustic signal-based method is the cheapest and provides reasonably accurate estimation as a result of many research efforts. Most of the acoustic-signal-based three-dimensional location estimators such as 3D sonic digitizer are using the ultrasound, and are organized with two procedures; time-of-flight (TOF) estimation and localization estimation. Since the errors in estimating the TOF could be accumulated with that of localization estimate, accuracy of TOF estimate is as...

• Radiation Oncology Journal
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• v.37 no.4
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• pp.259-264
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• 2019

Purpose: Accurate localization of the lumpectomy cavity during accelerated partial breast radiation (APBR) is essential for daily setup to ensure the prescribed dose encompasses the target and avoids unnecessary irradiation to surrounding normal tissues. Three-dimensional ultrasound (3D-US) allows direct visualization of the lumpectomy cavity without additional radiation exposure. The purpose of this study was to evaluate the feasibility of 3D-US in daily target localization for APBR. Materials and methods: Forty-seven patients with stage I breast cancer who underwent breast conserving surgery were treated with a 2-week course of APBR. Patients with visible lumpectomy cavities on high quality 3D-US images were included in this analysis. Prior to each treatment, X-ray and 3D-US images were acquired and compared to images from simulation to confirm accurate position and determine shifts. Volume change of the lumpectomy cavity was determined daily with 3D-US. Results: A total of 118 images of each modality from 12 eligible patients were analyzed. The average change in cavity volume was 7.8% (range, -24.1% to 14.4%) on 3D-US from simulation to the end-of-treatment. Based on 3D-US, significantly larger shifts were necessary compared to portal films in all three dimensions: anterior/posterior (p = 7E-11), left/right (p = 0.002), and superior/inferior (p = 0.004). Conclusion: Given that the lumpectomy cavity is not directly visible via X-ray images, accurate positioning may not be fully achieved by X-ray images. Therefore, when the lumpectomy cavity is visible on US, 3D-US can be considered as an alternative to X-ray imaging during daily positioning for selected patients treated with APBR, thus avoiding additional exposure to ionizing radiation.

• The Journal of the Acoustical Society of Korea
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• v.30 no.5
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• pp.255-264
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• 2011

The Head Related Transfer Function (HRTF) means a process related to acoustic transmission from 3d space to the listener's ear. In other words, it contains the information that human can perceive locations of sound sources. So, we make virtual 3d sound using HRTF, despite it doesn't actually exist. But, it can deteriorate some three-dimensional effect by the confusion between front and back directions due to the non-individual HRTF depending on each listener. In this paper, we proposed the new algorithm to reduce the confusion of sound image localization using human's acoustic characteristics. The frequency spectrum and global masking threshold of 3d sounds using HRTF are used to calculate the psychoacoustical differences among each directions. And perceptible cues in each critical band are boosted to create effective 3d sound. As a result, we can make the improved 3d sound, and the performances are much better than conventional methods.

• Radiation Oncology Journal
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• v.11 no.1
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• pp.167-174
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• 1993

Recently, stereotactic radiosurgery plan is required with the information of 3-D image and dose distribution. A project has been doing if developing LINAC based stereotactic radiosurgery since April 1991. The purpose of this research is to develop 3-D radiosurgery planning system using personal computer. The procedure of this research is based on two steps. The first step is to develop 3-D localization system, which input the image information of the patient, coordinate transformation, the position and shape of target, and patient contour into computer system using CT image and stereotactic frame. The second step is to develop 3-D dose planning system, which compute dose distribution on image plane, display on high resolution monitor both isodose distribution and patient image simultaneously and develop menu-driven planning system. This prototype of radiosurgery planning system was applied recently for several clinical cases. It was shown that our planning system is fast, accurate and efficient while making it possible to handle various kinds of image modalities such as angiography, CT and MRI. It makes it possible to develop general 3-D planning system using beam's eye view or CT simulation in radiation therapy in future.

• 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.