• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.61-66
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• 2006

This paper proposes a method for generating radar images used in ship handling simulator, which includes mathematical logics based on radar equations and information from Openflight format files. In order to make radar image much similar to that of real radar in PPI type, the proposed mathematical logic derives radar video signals under the consideration of riot only the data form flight format file of simulation scenes, but also geographical radar's position. The proposed method is considered useful to make radar images in ship handling simulator with accuracy and reality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.35-37
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• 2019

최근 딥 러닝의 급격한 발전과 함께 얼굴표정인식 기술이 상당한 진보를 이루었다. 그러나 기존 얼굴표정인식 기법들은 제한된 환경에서 취득한 인위적인 동영상에 대해 주로 개발되었기 때문에 실제 wild 한 환경에서 취득한 동영상에 대해 강인하게 동작하지 않을 수 있다. 이런 문제를 해결하기 위해 3D CNN, 2D CNN 그리고 RNN 의 새로운 결합으로 이루어진 Deep neural network 구조를 제안한다. 제안 네트워크는 주어진 동영상으로부터 두 가지 서로 다른 CNN 을 통해서 영상 내 공간적 정보뿐만 아니라 시간적 정보를 담고 있는 특징 벡터를 추출할 수 있다. 그 다음, RNN 이 시간 도메인 학습을 수행할 뿐만 아니라 상기 네트워크들에서 추출된 특징 벡터들을 융합한다. 상기 기술들이 유기적으로 연동하는 제안된 네트워크는 대표적인 wild 한 공인 데이터세트인 AFEW 로 실험한 결과 49.6%의 정확도로 종래 기법 대비 향상된 성능을 보인다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.185-188
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• 2019

3D 영상 데이터 중 하나인, 포인트 클라우드는 3 차원 데이터를 정밀하게 획득 할 수 있다는 장점으로 인해 군사, 교육, 의료, 건축 등의 다양한 분야에서 사용되고 있다. 특히, 자율 주행 분야에서 사용되는 동적 획득 포인트 클라우드는 광범위한 영역을 표현하므로 방대한 양의 데이터를 갖고 있어, 효율적인 압축이 필수적이다. 비디오 코덱을 활용하여 3 차원 데이터 압축을 진행하는 V - PCC 의 경우, 신뢰성과 범용성이 높다는 장점이 있으나, 2D 비디오 영상을 활용하기 때문에 대용량 및 광범위한 데이터의 압축이 불가능하다는 한계를 지니고 있다. 따라서, 본 논문에서는 V- PCC 의 한계를 극복하고, 광범위한 영역의 정보를 표현하는 동적 획득 포인트를 압축하기 위해 포인트 클라우드를 분할 및 양자화하는 방안을 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5669-5684
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• 2018

The new mobile edge network architecture has been required for an increasing amount of traffic, quality requirements, advanced driver assistance system for autonomous driving and new cloud computing demands on highway. This article proposes a hierarchical cloud computing architecture to enhance performance by using adaptive data load distribution for buses that play the role of edge computing server. A vehicular dynamic cloud is based on wireless architecture including Wireless Local Area Network and Long Term Evolution Advanced communication is used for data transmission between moving buses and cars. The main advantages of the proposed architecture include both a reduction of data loading for top layer cloud server and effective data distribution on traffic jam highway where moving vehicles require video on demand (VOD) services from server. Through the description of real environment based on NS-2 network simulation, we conducted experiments to validate the proposed new architecture. Moreover, we show the feasibility and effectiveness for the connected car media service on highway.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.24-32
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• 2024

Wearable metaverse devices have sparked enthusiasm as innovative virtual computing user interfaces by addressing a major source of user discomfort, namely, motion-to-photon latency. This kind of latency occurs between the user motion and screen update. To enhance the realism and immersion of experiences using metaverse devices, the vergence-accommodation conflict in stereoscopic image representation must be resolved. Ongoing research aims to address current challenges by adopting vari-focal, multifocal, and light field display technologies for stereoscopic imaging. We explore current trends in research with emphasis on multifocal stereoscopic imaging. Successful metaverse visualization services require the integration of stereoscopic image rendering modules and content encoding/decoding technologies tailored to these services. Additionally, real-time video processing is essential for these modules to correctly and timely process such content and implement metaverse visualization services.

• Journal of the Semiconductor & Display Technology
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• v.17 no.4
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• pp.21-26
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• 2018

Recently, the emergence of 3D cameras, 3D scanners and various cameras including Lidar is expected to be applied to applications such as AR, VR, and autonomous mobile vehicles that deal with 3D data. In Particular, the 3D point cloud data consisting of tens to hundreds of thousands of 3D points is rapidly increased in capacity compared with 2D data, Efficient encoding / decoding technology for smooth service within a limited bandwidth, and efficient service provision technology for differentiating the area of interest and the surrounding area are needed. In this paper, we propose a new quality parameter considering characteristics of 3D point cloud instead of quality change based on assumed video codec in MPEG V-PCC used in 3D point cloud compression, 3D Grid division method and representation for selectively transmitting 3D point clouds according to user's area of interest, and propose a new 3D Manifesto. By using the proposed technique, it is possible to generate more bitrate images, and it is confirmed that the efficiency of network, decoder, and renderer can be increased while selectively transmitting as needed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1869-1882
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• 1998

In this paper, we investigae convergence behaviors of a differential method for 2-D motion parameter estimation. While the differential method is widely studied for motion compensated prediction in video coding, little attention hs been paid to its convergence properties. Based on the nonseparable exponential covariance image model, we derive the estimates of update terms for the 2- and 6-parameter motion models. And, the effect of noise, spatial correlation, choice of spatial gradient measures, andthe size of a region, are quantitatively anlyzed in relation to the convergence speed. Some empirical results are presented to verify the analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.1A
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• pp.51-56
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• 2012

In order to reduce the complexity of HEVC, we propose a fast mode decision algorithm in depth videos. Since almost CU mode is decided as SKIP mode in depth-continuity regions, we design the algorithm using the property of depth videos. If cost of SKIP is smaller than the multiplication between the threshold for EarlySKIP and average cost of SKIP, EarlySKIP is performed. Otherwise, we calculate Inter $2N{\times}2N$. Then, if motion vector of Inter $2N{\times}2N$ is 0 and variance of CU is smaller than threshold for inter, we skip Inter $2N{\times}N$, Inter $N{\times}2N$. Experimental results show that our proposed algorithm reduces the encoding time from 39% to 82% with negligible PSNR loss and bitrate increase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2091-2098
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• 2010

This paper proposes a hologram data compression scheme that uses the existing image/video compression techniques, in which the existing techniques are modified appropriately to fit to the characteristics of hologram. In this paper we use CGH as the hologram data. The proposed scheme uses the generation characteristics of a CGH to consist of a pre-processing, spatial segmentation of a CGH, frequency-transformation with 2D-DCT (2-dimensional discrete cosine transform), and motion estimation and residual image generation in the frequency-domain. It uses H.264/AVC, the lossless compressor BinHex, and a linear quantizer that we have made. From the experiments the proposed scheme showed the image quality of about 25.4 dB at the compression ratio of 10:1 and about 16.5dB at 90:1 compression ratio.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.