• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.401-404
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• 2017

The 360 VR video has a format of a stereoscopic shape such as an isometric shape or a cubic shape or a cubic shape. Although these formats have different characteristics, they have in common that the resolution is higher than that of a normal 2D video. Therefore, it takes much longer time to perform coding/decoding on 360 VR video than 2D Video, so parallel processing techniques are essential when it comes to coding 360 VR video. HEVC, the state of art 2D video codec, uses Wavefront Parallel Processing (WPP) technology as a standard for parallelization. This technique is optimized for 2D videos and does not show optimal performance when used in 3D videos. Therefore, a suitable method for WPP is required for 3D video. In this paper, we propose WPP coding/decoding method which improves WPP performance on cube map format 3D video. The experiment was applied to the HEVC reference software HM 12.0. The experimental results show that there is no significant loss of PSNR compared with the existing WPP, and the coding complexity of 15% to 20% is further reduced. The proposed method is expected to be included in the future 3D VR video codecs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.560-570
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• 2013

In this paper, we propose transceiver design strategies for the two-cell multiple-input multiple-output (MIMO) interfering broadcast channel where inter-cell interference (ICI) exists in addition to inter-user interference (IUI). We first formulate the generalized zero-forcing interference alignment (ZF-IA) method based on the alignment of IUI and ICI in multi-dimensional subspace. We then devise a minimum weighted-mean-square-error (WMSE) method based on "regularizing" the precoders and decoders of the generalized ZF-IA scheme. In contrast to the existing weighted-sum-rate-maximizing transceiver, our method does not require an iterative calculation of the optimal weights. Because of this, the proposed scheme, while not designed specially to maximize the sum-rate, is computationally efficient and achieves a faster convergence compared to the known weighed-sum-rate maximizing scheme. Through analysis and simulation, we show the effectiveness of the proposed regularized ZF-IA scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.1C
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• pp.79-85
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• 2008

Dirty Paper Coding(DPC) can achieve the sum capacity of a multiuser multiple-input multiple-output(MU MIMO) broadcast channels. However, due to the high computational complexity of the successive encoding and decoding, deploying DPC in real systems is impractical. As one of practical alternatives to DPC, Block Diagonalization(BD) was researched. BD is an extension of the zero-forcing preceding technique that eliminates interuser interference(IUI) in downlink MIMO systems. Though BD has lower complexity than DPC, BD shows poor sum capacity performance. We show that sum capacity performance of BD is degraded due to no IUI constraint. Then, we modify BD to improve its sum capacity performance with relaxing the constraint and sub optimal channel set searching. With simulation results, it can be verified that our modification in BD induces some improvement in sum capacity performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1010-1019
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• 2016

The K-user multiple-input single-output broadcast channel is considered under per-antenna power constraints, i. e., each transmit antenna must satisfy its own power constraints. A low complexity zeroforcing(ZF) precoder is proposed when the number of transmit antennas M is greater than K. The proposed precoder design significantly reduces computational complexity for the precoder construction while attaining the sum spectral efficiency close to that achievable by the optimal ZF precoder.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.17-25
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• 2012

In this paper, we propose a method of producing a stereoscopic image from multiple images captured from a monoscopic camera. By translating a camera in the horizontal direction, left and right images are chosen among N captured images. For this, image edges are extracted and a rotational angle is estimated from edge orientation. Also, a translational vector is also estimated from the correlation of projected image data. Then, two optimal images are chosen and subsequently compensated using the rotational angle as well as the translational vector in order to make a satisfactory stereoscopic image. The proposed method was performed on thirty-two test image set. The subjective visual fatigue test was carried out to validate the 3D quality of stereoscopic images. In terms of visual fatigue, the 3D satisfaction ratio reached approximately 84%.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.195-198
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• 2012

The N basis functions are typically chosen so that Surface reflectance functions(SRFs) and spectral power distributions (SPDs) can be accurately reconstructed from their N-dimensional vector codes. Typical rendering applications assume that the resulting mapping is an isomorphism where vector operations of addition, scalar multiplication, component-wise multiplication on the N-vectors can be used to model physical operations such as superposition of lights, light-surface interactions and inter-reflection. The vector operations do not mirror the physical. However, if the choice of basis functions is restricted to characteristic functions then the resulting map between SPDs/SRFs and N-vectors is anisomorphism that preserves the physical operations needed in rendering. This paper will show how to select optimal characteristic function bases of any dimension N (number of basis functions) and also evaluate how accurately a large set of Munsell color chips can approximated as basis functions of dimension N.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1122-1133
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• 2019

We have designed and implemented a new data processing framework called MOHA(Mtc On HAdoop) which can effectively support Many-Task Computing(MTC) applications in a YARN-based Hadoop platform. MTC applications can be composed of a very large number of computational tasks ranging from hundreds of thousands to millions of tasks, and each MTC application may have different resource usage patterns. Therefore, we have implemented MOHA-TaskExecutor(a pilot-job that executes real MTC application tasks)'s Adaptive Parallel Computability which can adaptively execute multiple tasks simultaneously, in order to improve the parallel computability of a YARN container and the overall system throughput. We have implemented multi-threaded version of TaskExecutor which can "independently and dynamically" adjust the number of concurrently running tasks, and in order to find the optimal number of concurrent tasks, we have employed Hill-Climbing algorithm.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.602-612
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• 2019

Various streaming technologies are being studied to guarantee the QoE of viewers due to the development of realistic media. HTTP adaptive streaming is a typical example, and it is based on HTTP / 1.1 and TCP. These protocols have become one of the causes of delaying the image delay and increasing the waiting time of web pages. Therefore, in this paper, we propose a QUIC-DASH system applying the UDP-based transmission protocols QUIC and HTTP / 2 to the MPEG-DASH system after analyzing various transmission protocols and development process of HTTP. Through experiments, the QUIC-DASH system confirmed the possibility of providing optimal performance in terms of transmission speed of LTE environment than existing system. We also suggest various future studies for better performance.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.58-66
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• 2019

Recognition of named entity such as proper nouns in conversation sentences is the most fundamental and important field of study for efficient conversational information prediction. The most important part of a task-oriented dialogue system is to recognize what attributes an object in a conversation has. The named entity recognition model carries out recognition of the named entity through the preprocessing, word embedding, and prediction steps for the dialogue sentence. This study aims at using user - defined dictionary in preprocessing stage and finding optimal parameters at word embedding stage for efficient dialogue information prediction. In order to test the designed object name recognition model, we selected the field of daily chemical products and constructed the named entity recognition model that can be applied in the task-oriented dialogue system in the related domain.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.264-272
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• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.