• Journal of Broadcast Engineering
• /
• v.21 no.1
• /
• pp.76-86
• /
• 2016

This study was investigated whether the perceived depth was changed depending on the measurement methods. In the method of direct comparison, virtual object with one of the various binocular disparities was presented in the frontal space with LEDs which were used for depth estimation for a binocular stimulus, while in the method of indirect comparison, visual object was presented in the frontal space but the LEDs were placed rightward at the angle of 45 degree from the mid-sagittal line. In these experimental setup, the depth of binocular stimulus was directly matched that of LED in direct comparison condition. In indirect comparison condition, however, observer estimated the depth of binocular stimulus, turned one's head rightward to the array of LEDs and turned on the LED which was supposed to be the same depth as binocular stimulus. Additionally, it was investigated whether the perceived depth was different depending on observer's stereo acuity. The results showed that perceived depths measured in the direct comparison were more similar to the depth predicted from geometry than those in the indirect comparison, and that the perceived depths from observers with high stereo acuity were similar to the predicted depth from geometry those from observers with low stereo acuity. These results indicated that stereoscopic depths of the binocular stimuli would vivid and compelling when binocular stimuli was simultaneously presented with real objects in the same visual space, like a mixed reality.

• Journal of the Korea Computer Graphics Society
• /
• v.24 no.1
• /
• pp.19-26
• /
• 2018

In this paper, we propose a gaze depth estimation method based on a binocular eye tracker for virtual reality and augmented reality applications. The proposed gaze depth estimation method collects a wide range information of each eye from the eye tracker such as the pupil center, gaze direction, inter pupil distance. It then builds gaze estimation models using Multilayer perceptron which infers gaze depth with respect to the eye tracking information. Finally, we evaluated the gaze depth estimation method with 13 participants in two ways: the performance based on their individual models and the performance based on the generalized model. Through the evaluation, we found that the proposed estimation method recognized gaze depth with 90.1% accuracy for 13 individual participants and with 89.7% accuracy for including all participants.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.10 no.6
• /
• pp.95-104
• /
• 2006

The presence of cavitations under pavements or behind tunnel linings of concrete is likely to result in collapse. One method of detecting such voids by non-destructive means is low frequency type radar(GPR). By the way, the size and thickness of small cavitation can't be detected by the present radar technology with low frequency and low resolution when it apply to civil structures like that. To overcome these problems and limitations, this study aims to develope and propose a new analysis method for estimating the depth, cross-sectional size and thickness of cavitations using low frequency radar. A new proposed method is based on the experiments that are carried out for analyzing the correlation between the measurement values(the amplitudes of radar return) of low frequency radar and various type of cavitations. In this process, the threshold value for radar image processing which aims to represent only cavitations to be fitted size can be obtained. As the results, it is clarified that a proposed method has a possibility of estimating cavitation depth, size and thickness with good accuracy in laboratory scale.

• Journal of Broadcast Engineering
• /
• v.27 no.3
• /
• pp.341-350
• /
• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.

• Geophysics and Geophysical Exploration
• /
• v.10 no.1
• /
• pp.77-88
• /
• 2007

Following a successful bathymetric mapping demonstration in a previous study, the potential of airborne EM for seafloor characterisation has been investigated. The sediment thickness inferred from 1D inversion of helicopter-borne time-domain electromagnetic (TEM) data has been compared with estimates based on marine seismic studies. Generally, the two estimates of sediment thickness, and hence depth to resistive bedrock, were in reasonable agreement when the seawater was ${\sim}20\;m$ deep and the sediment was less than ${\sim}40\;m$ thick. Inversion of noisy synthetic data showed that recovered models closely resemble the true models, even when the starting model is dissimilar to the true model, in keeping with the uniqueness theorem for EM soundings. The standard deviations associated with shallow seawater depths inferred from noisy synthetic data are about ${\pm}5\;%$ of depth, comparable with the errors of approximately ${\pm}1\;m$ arising during inversion of real data. The corresponding uncertainty in depth-to-bedrock estimates, based on synthetic data inversion, is of order of ${\pm}10\;%$. The mean inverted depths of both seawater and sediment inferred from noisy synthetic data are accurate to ${\sim}1\;m$, illustrating the improvement in accuracy resulting from stacking. It is concluded that a carefully calibrated airborne TEM system has potential for surveying sediment thickness and bedrock topography, and for characterising seafloor resistivity in shallow coastal waters.

• Korean Journal of Soil Science and Fertilizer
• /
• v.39 no.2
• /
• pp.109-115
• /
• 2006

Understanding characteristics of claypan soils has long been an issue for researchers and farmers because the high-clay subsoil has a pronounced effect on grain crop productivity. The claypan restricts water infiltration and storage within the crop root zone, but these effects are not uniform within fields. Conventional techniques of identifying claypan soil characteristics require manual probing and analysis which can be quite expensive; an expense most farmers are unwilling to pay. On the other hand, farmers would be very interested if this information could be obtained with easy-to-use field sensors. Two examples of sensors that show promise for helping in claypan soil characterization are soil profile strength sensing and bulk soil apparent electrical conductivity (ECa). Little has been reported on claypan soils relating the combined information from these two sensors with grain crop yield. The objective of this research was to identify the relationships of sensed profile soil strength and soil EC with nine years of crop yield (maize and soybean) from a claypan soil field in central Missouri. A multiple-probe (five probes on 19-cm spacing) cone penetrometer was used to measure soil strength and an electromagnetic induction sensor was used to measure soil EC at 55 grid site locations within a 4-ha research field. Crop yields were obtained using a combine equipped with a yield monitoring system. Soil strength at the 15 to 45 cm soil depth were significantly correlated to crop yield and ECa. Estimated crop yields from apparent electrical conductivity and soil strength were validated with an independent data set. Using measurements from these two sensors, standard error rates for estimating yield ranged from 9 to 16%. In conclusion, these results showed that the sensed profile soil strength and soil EC could be used as a measure of the soil productivity for grain crop production.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.22 no.2
• /
• pp.92-101
• /
• 2020

To prevent and mitigate damage to farms due to heavy snowfall, snow weight information should be provided in addition to snow depth. This study reviews four formulae regarding snow density and weight used in extant studies and applies them in Suwon area to estimate snow weight in Korea. We investigated the observed snow depth of 94 meteorological stations and automatic weather stations (AWS) data over the past 30 years (1988-2017). Based on the spatial distribution of snow depth by area in Korea, much of the fresh snow cover, due to heavy snowfall, occurred in Jeollabuk-do and Gangwon-do. Record snowfalls occurred in Gyeongsangbuk-do and Gangwon-do. However, the most recent heavy snowfall in winter occurred in Gyeonggi-do, Gyeongsangbuk-do, and Jeollanam-do. This implies that even if the snow depth is high, there is no significant damage unless the snow weight is high. The estimation of snow weight in Suwon area yielded different results based on the calculation method of snow density. In general, high snow depth is associated with heavy snow weight. However, maximum snow weight and maximum snow depth do not necessarily occur on the same day. The result of this study can be utilized to estimate the snow weight at other locations in Korea and to carry out snow weight prediction based on a numerical model. Snow weight information is expected to aid in establishing standards for greenhouse design and to reduce the economic losses incurred by farms.

• Journal of the Korean earth science society
• /
• v.44 no.6
• /
• pp.594-610
• /
• 2023

The horizontal-to-vertical spectral ratio (HVSR) has been widely applied to evaluate ground characteristics such as site response and thickness of the soft sedimentary layer on top of the bedrock via dominant frequencies and amplification factors of microtremors. Eight seismic stations were selected to investigate the HVSR results at the surface and at varying depths, and their variations due to wind speeds. These stations are equipped with seismic sensors on the surface and downhole(s) at depths. The borehole data analysis reveals that the geological condition at burial depth influences the HVSR results. Their dominant frequencies indicate the entire thickness of the soft layer, not the thickness to the bottom or top of the soft sedimentary layer from the seismometer burial depth. Analysis of the background noise observed at the surface showed that the resonance frequency estimation varied with wind speed changes. In the studied cases, the background noise observed in the sedimentary layer at depths of 20 to 66 meters yielded stable and consistent resonance frequency estimation regardless of wind speed fluctuations. The results of the seismic sensors buried deeper than 100 meters are unstable. The result indicates that the background noise from the buried seismometer at shallow depths (~0.3 m) under light wind conditions (wind speeds less than 3 m/s) is sufficient to achieve the purpose of the HVSR analysis.

• Geophysics and Geophysical Exploration
• /
• v.15 no.2
• /
• pp.51-56
• /
• 2012

One of the most critical and essential procedures in the interpretation of gravity and magnetic data is to separate the anomaly due to the specific geologic structure from the summation of effects from a broad variety of geologic sources, especially those of different depths. Separation of the residual anomaly from the regional field is the most simple case of the vertical separation. If the anomaly due to a layer of specific depth can be separated or the depth of the separated layer can be quantitatively determined, it may deserve the separation-sounding. We suggest a wavelength filter whose cutoff frequency is determined by log-power spectrum analysis, as a separation-sounding filter. We applied this filter both to synthetic and real gravity data acquired at Heunghae area, and compared the results with those of Jacobsen's upward continuation filter. These showed that the proposed separation-sounding filter could be a useful tool for interpretation of the vertical geologic structure by stripping the gravity effects of geologic sources down to the desired depth.

• Journal of Digital Convergence
• /
• v.11 no.1
• /
• pp.243-248
• /
• 2013

In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.