• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.232-235
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• 2010

This paper proposes an efficient depth-map coding method. The adaptive block-based depth-map coding method decides the number of bit planes to be encoded according to the quantization parameters to obtain the desired bit rates. So, the depth-map coding using the block-based decision of the bit-plane to be encoded proposes to free from the constraint of the quantization parameters. Simulation results show that the proposed method, in comparison with the adaptive block-based depth-map coding method, improves the average BD-rate savings by 3.5% and the average BD-PSNR gains by 0.25dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2C
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• pp.186-193
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• 2009

Multi-view video is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This paper proposed enhanced compression method by presentation of efficient layered depth image using real distance comparison, solution of overlap problem, and YCrCb color transformation. In experimental results, confirmed high compression performance and good reconstructed image.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.484-492
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• 2016

The High efficiency video coding (HEVC) is the newest video coding standard that achieves coding efficiency higher than previous video coding standards such as H.264/AVC. In intra prediction, the prediction units (PUs) are derived from a large coding unit (LCU) which is partitioned into smaller coding units (CUs) sizing from 8x8 to 64x64 in a quad-tree structure. As they are divided until having the minimum depth, Optimum CU splitting is selected in RDO (Rate Distortion Optimization) process. In this process, HEVC demands high computational complexity. In this paper, to reduce the complexity of HEVC, we propose a fast CU mode decision (FCDD) for intra prediction by using FAST (Features from Accelerated Segment Test) corner detection. The proposed method reduces computational complexity with 53.73% of the computational time for the intra prediction while coding performance degradation with 0.7% BDBR is small compared to conventional HEVC.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.147-161
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• 2022

Video on demand (VOD) platforms provide immersive, inspiring, and commercial-free binge watching experiences. Recently, the number of these platform users increased dramatically as users can enjoy various contents without physical and time constraints during COVID-19. However, such platforms do not provide sufficient video censorship services while there is a strong need. In this study, we investigated the users' desire for video censorship when choosing and watching movies on VOD platforms, and how video censorship can be applied to different types of scenes to increase the censoring effect without diminishing the enjoyment. We first conducted an online survey with 98 respondents to identify the types of discomfort while watching sexual, violent, or drug-related scenes. We then conducted an in-depth online interview with 18 participants to identify the effective video filtering types and regions for each of the three scenes. Based on the findings, we suggest implications for designing a censor application for videos that contain uncomfortable scenes.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.85-90
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• 2007

세계 이동 통신 시장은 점차 3G(세대)~3.5G(세대)로 전환되면서 세대 교체하고 있다. 3G 이동 통신의 대표 서비스인 화상전화는 음성통화와는 다른 새로운 커뮤니케이션이나 여러 가지 원인으로 일반화되지 않고 있는데, 그 원인 중 하나가 새로운 사용 경험과 사용 환경이 충분히 고려되지 않은 UI 라고 생각된다. 따라서, 본 조사에서는 한국, 일본, 영국, 이탈리아 등 4 개국을 대상으로 현재 출시된 화상전화 제품에 대하여 실사용자 FGI 와 설문, In-depth interview 등을 통해 사용자들의 화상전화 사용 경험을 조사하고, 조사를 통한 발견점을 통해 UI 설계 전문가 관점에서 향후 UI 에 대한 제안점을 찾아 보다 나은 화상전화 경험을 제공하기 위한 바탕으로 삼고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.42-45
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• 2011

최근ISO/IEC와 ITU는 공동 협력팀(Joint Collaborative Team on Video Coding-JCT-VC)을 구성하여 HEVC(High Efficiency Video Coding)라 불리는 새로운 비디오 압축 표준 기술을 개발하고 있다. JCT-VC의 목표 중 하나는 H.264/AVC 압축률의 2배를 향상하는 것으로 최근 HEVC 테스트 모델(HEVC Test Model - HM)을 확정했다. HM의 여러 기술 중에서 확장 블록 구조 (large block structure) 기술은 CU(Coding Unit)와 TU(Transform Unit), PU(Partition Unit)로 구성된다. CU와 TU는 압축 단위와 변환 기술을 확장한 반복적인 문법구조(recursive syntax structure)이며, PU는 H.264/AVC과 동일한 형태를 띈다. 확장 블록 구조는 CU, PU, TU의 여러 조합에 의해 다양한 모드를 지원하여 압축 성능은 높아졌지만 HM 부호화기의 복잡도는 증가한다. 본 논문에서는 HM에 채택된 확장 블록 구조 기술에 대해 설명한 후, 계층적 B프레임 구조로 부호화 되는 경우 이전 레벨의 CU Depth 정보를 이용하여 현재 레벨의 CU Depth를 효과적으로 제한하여 기존의 방법보다 빠르게 부호화하는 방법을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1405-1412
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• 2015

Recently, Due to the rapid growth of broadcasting communication and video coding technologies, the demands for immersive media contents based on 3D stereoscopic video will increase steadily. And the demands must ultimately provide the contents for users which are in wireless channel such as vehicle, train, and ship. Thus, in this paper, we transmit the 3D stereoscopic video over the maritime Rician channel that direct wave is more dominant than reflective wave. Besides, we present unequel error protection (UEP) by applying hierarchical 4/16-QAM to V+D(Video plus Depth) format which can represent 3D stereoscopic video. We expect our system to provide seamless broadcasting service for users with poor reception condition.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1762-1773
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• 2014

In this paper, a distributed image coding scheme for multi-view video through an efficient generation of side information is proposed. A distributed video coding technique corrects the errors in the side information, which is generated with the original image, by using the channel coding technique at the decoder. Therefore, the more correct the generated side information is, the better the performance of distributed video coding. The proposed technique is to apply the distributed video coding schemes to the image coding for multi-view video. It generates side information by selectively and efficiently using both 3-dimensional warping based on the depth map with spatially adjacent frames and motion-compensated temporal interpolation with temporally adjacent frames. In this scheme the difference between the adjacent frames, the sizes of the motion vectors for the adjacent blocks, and the edge information are used as the selection criteria. From the experiments, it was observed that the quality of the side information generated by the proposed technique was improved by the average peak signal-to-noise ratio of 0.97dB than the one by motion-compensated temporal interpolation or 3-dimensional warping. The result from analyzing the rate-distortion curves revealed that the proposed scheme could reduce the bit-rate by 8.01% on average at the same peak signal-to-noise ratio value, compared to previous work.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.129-135
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• 2011

In this paper, we propose the algorithm using optical flow and machine learning-based segmentation for the 3D conversion of 2D video. For the segmentation allowing the successful 3D conversion, we design a new energy function, where color/texture features are included through machine learning method and the optical flow is also introduced in order to focus on the regions with the motion. The depth map are then calculated according to the optical flow of segmented regions, and left/right images for the 3D conversion are produced. Experiment on various video shows that the proposed method yields the reliable segmentation result and depth map for the 3D conversion of 2D video.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2767-2780
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• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.