• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.123-132
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• 2011

Recently, DVC (Distributed Video Coding) is receiving a lot of attention as one of the low complexity video encoding techniques suitable for various applications with computation-limited and/or power-limited environment, and is being actively studied for improving the coding efficiency. This paper proposes a rate-distortion based selective block encoding scheme. First, the motion information is obtained in the process of generating side information at decoder and received through the feedback channel, and then, based on this information, the proposed method performs a selective block encoding based on rate-distortion optimization. Experimental results show that the performance of the proposed scheme reaches up to 2.2 dB PSNR gain over the existing scheme. Moreover, it is shown that the complexity can be reduced by encoding parts of region considering rate-distortion cost.

• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.3-16
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• 2015

Will orange scent enhance video reality if it is presented with a video which vividly illustrates orange juice? Or, will romantic scent improve video reality if it is presented along with a date scene? Whereas the former is related to reality improvement when concrete objects or places are present in a video, the latter is related to a case when they are absent. This paper reviews previous research which tested diverse videos and scents in order to answer the above two different questions, and discusses implications, limitations, and future research directions. In particular, this paper focuses on measurement methods and results regarding acceptability of olfactory information, perception of scent similarity, olfactory vividness and video reality, matching between scent vs. color (or color temperature), and description of various scents using emotional adjectives. We expect this paper to help researchers or engineers who are interested in using scents for video reality.

• International Journal of Contents
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• v.10 no.3
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• pp.9-16
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• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.16-25
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• 2015

Even if the demands for ultra-high-quality multimedia contents are increasing, it is difficult to produce, encode, play and transport ultra-high-quality contents under the existing broadcasting environment. By the reason, various technologies for the UHD contents have been developed in order to satisfy the user's needs. In this paper, we propose a design methodology of a broadcasting system, which consists of two parts, for UHD services with two parts. At the transmit part of the proposed system can encode a video into several layered-bitstreams hierarchically, and then transport each bitstream over heterogeneous networks. The receiver part can play the received video by composing the separated bitstreams. The proposed system can adaptively provide both HD and UHD contents according to user's reception conditions by using the heterogeneous networks.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.189-194
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• 2018

This study reflects the current trend of the blind hiring culture focused on job competency rather than education specification as government initiative. In order to overcome the limitation of the existing document-oriented online recruitment process, we proposed a system architecture design of video interview system. In addition, we have evaluated the effectiveness through the development of prototype and performance experiment based on it. The proposed online video interview system is designed to combine intelligent Web technology to enable customized job matching and distant job coaching. This system is designed to reduce recruitment cost and opportunity cost of job seekers. Based on results derived from this study, commercialization of the proposed video interview system can be expected to be an practical online recruitment solution for the job competency based employment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.37-43
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• 2009

Streaming video service over wireless and mobile communication networks has received significant interests from both academia and industry recently. Specifically, mobile WiMAX (IEEE 802.16e) is capable of providing high data rate and flexible Quality of Service (QoS) mechanisms, supporting mobile streaming very attractive. However, we need to note that streaming videos can be partially deteriorated in their macroblocks and/or slices owing to errors on OFDMA subcarriers, as we consider that compressed video sequence is generally sensitive to the error-prone channel status of the wireless and mobile network. In this paper, we introduce an OFDMA subcarrier-adaptive mobile streaming server based on cross-layer design. This streaming server system is substantially efficient to reduce the deterioration of streaming video transferred on the subcarriers of low power strength without any modifications of the existing schedulers, packet ordering/reassembly, and subcarrier allocation strategies in the base station.

• Journal of Digital Convergence
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• v.16 no.2
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• pp.335-341
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• 2018

This study is a study on effective stitching technique for video recorded by using a dual-lens $360^{\circ}$ camera composed of two fisheye lenses. First of all, this study located a problem in the result of stitching by using a bundled program. And the study was carried out, focusing on looking for a stitching technique more efficient and closer to perfect by comparatively analyzing the results of stitching by using Autopano Video Pro and Autopano Giga, professional stitching program. As a result, it was shown that the problems of bundled program were horizontal and vertical distortion, exposure and color mismatch and unsmooth stitching line. And it was possible to solve the problem of the horizontal and vertical by using Automatic Horizon and Verticals Tool of Autopano Video Pro and Autopano Giga, problem of exposure and color by using Levels, Color and Edit Color Anchors and problem of stitching line by using Mask function. Based on this study, it is to be hoped that $360^{\circ}$ VR video content closer to perfect can be produced by efficient stitching technique for video recorded by using dual-lens $360^{\circ}$ camera in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.416-419
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• 2015

In this paper, we propose an effective design of transform hardware for real-time HEVC(High Efficiency Video Coding) encoder. HEVC encoder determines the transform mode($4{\times}4$, $8{\times}8$, $16{\times}16$, $32{\times}32$) by comparing RDCost. RDCost require a significant amount of computation and time because it is determined by bit-rate and distortion which is computated via transform, quantization, dequantization, and inverse transform. This paper therefore proposes a new method for transform mode determination using sum of transform coefficient. Also, proposed hardware architecture is implemented with multiplexer, recursive adder/subtracter, and shifter only to derive reduction of the computation. Proposed method for transform mode determination results in an increase of 0.096 in BD-PSNR, 0.057 in BD-Bitrate, and decrease of 9.3% in encoding time by comparing HM 10.0. The hardware which is proposed is implemented by 256K logic gates in TSMC 130nm process. Its maximum operation frequency is 200MHz. At 140MHz, the proposed hardware can support 4K Ultra HD video encoding at 60fps in real time.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.6-29
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• 2020

Biometrics identification using multiple modalities has attracted the attention of many researchers as it produces more robust and trustworthy results than single modality biometrics. In this paper, we present a novel multimodal recognition system that trains a deep learning network to automatically learn features after extracting multiple biometric modalities from a single data source, i.e., facial video clips. Utilizing different modalities, i.e., left ear, left profile face, frontal face, right profile face, and right ear, present in the facial video clips, we train supervised denoising auto-encoders to automatically extract robust and non-redundant features. The automatically learned features are then used to train modality specific sparse classifiers to perform the multimodal recognition. Moreover, the proposed technique has proven robust when some of the above modalities were missing during the testing. The proposed system has three main components that are responsible for detection, which consists of modality specific detectors to automatically detect images of different modalities present in facial video clips; feature selection, which uses supervised denoising sparse auto-encoders network to capture discriminative representations that are robust to the illumination and pose variations; and classification, which consists of a set of modality specific sparse representation classifiers for unimodal recognition, followed by score level fusion of the recognition results of the available modalities. Experiments conducted on the constrained facial video dataset (WVU) and the unconstrained facial video dataset (HONDA/UCSD), resulted in a 99.17% and 97.14% Rank-1 recognition rates, respectively. The multimodal recognition accuracy demonstrates the superiority and robustness of the proposed approach irrespective of the illumination, non-planar movement, and pose variations present in the video clips even in the situation of missing modalities.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.413-419
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• 2018

Nowadays, smart phone became an important part of communication media and integrated into people's life. If callers rely on helmet-mounted display(HMD) augmented reality technique to add two-way user's facial expression, appearance, actions during the calling process, it will let callers have a visualized fantastic sensual experience. And through that method can break the limitations of vision, so research that technical problem can promote the development of visual arts, that is meaningful. This paper will choose and composite several existed technologies to set up two hypothesis, try to realize AR video calling. Through comparison and analysis to find those two hypothesis' problem, and create design solutions to solve problems. And use case study method to present two cases for prove my paper's result that is those two hypothesis can be realize in future. Use those technologies can bring more convenience and enjoyment to people's life. It can be predicted that AR video calling process can be successfully realized and will have unlimited development in future.