• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.197-200
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• 2011

In this paper, we propose a multi-view stereoscopic image synthesis algorithm for 3DTV system using depth information with an RGB texture from a depth camera. The proposed algorithm synthesizes multi-view images which a virtual convergence camera model could generate. Experimental results showed that the performance of the proposed algorithm is better than those of conventional methods.

• KSCI Review
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• v.14 no.1
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• pp.231-239
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• 2006

Geographic information system (GIS) geography reference it talks the software system which is possible. When like this geographic information system in key feature trying to observe the problem which is an expression of geography information in the center, the research and development with 3 dimension expressions is active from 2 dimension expressions of existing and it is advanced. double meaning geography information which is huge to be quick, the place where it controls efficiently there is a many problem, the ring from the dissertation which it sees and 3 dimensions and efficient scene of the GIS rendering compared to the ring from hazard image base modeling and rendering compared to hazard proposal LDI (Layered Depth Images) it uses GIS rendering compared to the ring to sleep it does. It acquired the terrain data of 3 dimensions from thread side base method. terrain data of 3 dimensions which are acquired like this the place where it has depth information like this depth information in base and the LDI, it did it created. Also it was a traditional modeling method and 3DS-Max it used and it created the LDI. It used LDI information which is acquired like this and the GIS of more efficient 3 dimensions rendering compared to the possibility of ring it was.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.1029-1030
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• 2007

I introduce two experiments that investigate temporal factors of stereopsis: one is for depth perception and the other is for perception of motion in depth. Both studies show that there are multiple mechanisms to process depth information with different temporal characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.111-118
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• 2006

A hybrid focus method with multiple laser slits is newly proposed for the measurement of surface morphology with depth discontinuity, and it is based on the integration of DFB and DFF. Rough depth information is estimated through calibration tables which are constructed by DFD with multiple laser slits, and then DFF is applied to only each specific depth range using the rough depth information resulting from DFD. The proposed hybrid method gives more accurate results than DFD and DFF, and faster measurement than DFF in the vicinity of depth discontinuity Its performance is verified through experiments of calibration blocks with sharp depth discontinuity.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.774-779
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• 2016

The conventional methods using color signal for tracking the movement of the object require a lot of calculation and the performance is not accurate. In this paper, we propose a method to effectively track the moving objects using the depth information from a depth camera. First, it separates the background and the objects based on the depth difference in the depth of the screen. When an object is moved, the depth value of the object becomes blurred because of the phenomenon of Motion Blur. In order to solve the Motion Blur, we observe the changes in the characteristics of the object (the area of the object, the border length, the roundness, the actual size) by its velocity. The proposed algorithm was implemented in the simulation that was applied directly to the tracking of a golf ball. We can see that the estimated value of the proposed method is accurate enough to be very close to the actual measurement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.242-259
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• 2015

Three-dimensional video coding is one of the main challenges restricting the widespread applications of 3D video and free viewpoint video. In this paper, a novel fractal coding algorithm with motion-vector-field-based motion estimation for depth map sequence is proposed. We firstly add pre-search restriction to rule the improper domain blocks out of the matching search process so that the number of blocks involved in the search process can be restricted to a smaller size. Some improvements for motion estimation including initial search point prediction, threshold transition condition and early termination condition are made based on the feature of fractal coding. The motion-vector-field-based adaptive hexagon search algorithm on the basis of center-biased distribution characteristics of depth motion vector is proposed to accelerate the search. Experimental results show that the proposed algorithm can reach optimum levels of quality and save the coding time. The PSNR of synthesized view is increased by 0.56 dB with 36.97% bit rate decrease on average compared with H.264 Full Search. And the depth encoding time is saved by up to 66.47%. Moreover, the proposed fractal depth map sequence codec outperforms the recent alternative codecs by improving the H.264/AVC, especially in much bitrate saving and encoding time reduction.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.659-664
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• 2005

Advanced countries overhaul government workflows using IT, which not only enhances efficiency and productivity, but paves the way to a 'e-Government' offering prompt, quality service for citizens. This research analyzes the DiD(Defense-in-Depth Strategy) and compares the information protection strategy of Korean e-Government with DiD for reliable and safe e-Government's build.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.8-14
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• 2018

In the field of surveillance cameras, it is possible to increase the people detection accuracy by using depth information indicating the distance between the camera and the object. In general, depth information is obtained by calculating the parallax information of the stereo camera. However, this method is difficult to operate in real time in the embedded environment due to the large amount of computation. Jetson TX2, released by NVIDIA in March 2017, is a high-performance embedded board with a GPU that enables parallel processing using the GPU. In this paper, a stereo camera is installed in Jetson TX2 to acquire depth information in real time, and we proposed a people counting method using acquired depth information. Experimental results show that the proposed method had a counting accuracy of 98.6% and operating in real time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.827-833
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• 2012

In this paper, we propose an improved optical flow algorithm which reduces computational complexity as well as noise level. This algorithm reduces computational time by applying level simplification technique and removes noise by using eigenvectors of objects. Optical flow is one of the accurate algorithms used to generate depth information from two image frames using the vectors which track the motions of pixels. This technique, however, has disadvantage of taking very long computational time because of the pixel-based calculation and can cause some noise problems. The level simplifying technique is applied to reduce the computational time, and the noise is removed by applying optical flow only to the area of having eigenvector, then using the edge image to generate the depth information of background area. Three-dimensional images were created from two-dimensional images using the proposed method which generates the depth information first and then converts into three-dimensional image using the depth information and DIBR(Depth Image Based Rendering) technique. The error rate was obtained using the SSIM(Structural SIMilarity index).