• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.136-139
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• 2017

Recently, many companies and consumers has shown a lot of interest toward VR(Virtual Reality), so many VR devices such as HMD(Head mounted Display) and 360 degree VR camera are released on the market. Current encoded 360 degree VR video uses the codec which originally made for the conventional 2D video. Therefore, the compression efficiency isn't optimized because the en/decoder does not consider the characteristics of the 360 degree VR video. In this paper, we propose a method to improve the compression efficiency by using the reference frame which compensates for the distortions caused by characteristics the 360 degree VR video. Applying the proposed method we were able to increase the compression efficiency by providing better prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4372-4394
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• 2020

The distribution of popular videos incurs a large amount of traffic at the base stations (BS) of networks. Device-to-multi-device (D2MD) communication has emerged an efficient radio access technology for offloading BS traffic in recent years. However, traditional studies have focused on synchronous user requests whereas asynchronous user requests are more common. Hence, offloading BS traffic in case of asynchronous user requests while considering their time-varying characteristics and the quality of experience (QoE) of video request users (VRUs) is a pressing problem. This paper uses social stability (SS) and video loading duration (VLD)-tolerant property to group VRUs and seed users (SUs) to offload BS traffic. We define the average amount of data transmission (AADT) to measure the network's capacity for offloading BS traffic. Based on this, we formulate a time-varying bipartite graph matching optimization problem. We decouple the problem into two subproblems which can be solved separately in terms of time and space. Then, we propose the socially aware D2MD user selection (SA-D2MD-S) algorithm based on finite horizon optimal stopping theory, and propose the SA-D2MD user matching (SA-D2MD-M) algorithm to solve the two subproblems. The results of simulations show that our algorithms outperform prevalent algorithms.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.177-186
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• 2004

It is a weak point of the motion estimation technique for video compression that the predicted video encoding algorithm requires higher-order computational complexity. To reduce the computational complexity of encoding algorithms, researchers introduced techniques such as 3D-WT that don't require motion prediction. One of the weakest points of previous 3D-WT studies is that they require too much memory for encoding and too long delay for decoding. In this paper, we propose a technique called `FS (Fast playable and Scalable) 3D-WT' This technique uses a modified Haar wavelet transform algorithm and employs improved encoding algorithm for lower memory and shorter delay requirement. We have executed some tests to compare performance of FS 3D-WT and 3D-V. FS 3D-WT has exhibited the same high compression rate and the same short processing delay as 3D-V has.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.2
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• pp.281-288
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• 2016

The natural moving objects are the most non-rigid shapes with randomly time-varying deformation, and its types also very diverse. Methods of non-rigid shape reconstruction have widely applied in field of movie or game industry in recent years. However, a realistic approach requires moving object to stick many beacon sets. To resolve this drawback, non-rigid shape reconstruction researches from input video without beacon sets are investigated in multimedia application fields. In this regard, our paper propose novel CPSRF(Chained Partial Stereo Rigid Factorization) algorithm that can reconstruct a non-rigid 3D shape. Our method is focused on the real-time reconstruction of non-rigid 3D shape and motion from stereo 2D video sequences per frame. And we do not constrain that the deformation of the time-varying non-rigid shape is limited by a Gaussian distribution. The experimental results show that the 3D reconstruction performance of the proposed CPSRF method is superior to that of the previous method which does not consider the random deformation of shape.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.44-53
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• 2011

In this paper, we propose a 3D conversion algorithm of 2D video using depth layer partition method. In the proposed algorithm, we first set frame groups using cut detection algorithm. Each divided frame groups will reduce the possibility of error propagation in the process of motion estimation. Depth image generation is the core technique in 2D/3D conversion algorithm. Therefore, we use two depth map generation algorithms. In the first, segmentation and motion information are used, and in the other, edge directional histogram is used. After applying depth layer partition algorithm which separates objects(foreground) and the background from the original image, the extracted two depth maps are properly merged. Through experiments, we verify that the proposed algorithm generates reliable depth map and good conversion results.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.243-248
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• 2013

In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.286-295
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• 2012

To meet the increased demand of video-on-demand (VoD) services, peer-to-peer (P2P) mesh-based multiple video approaches have been recently proposed, where each peer is able to find a video segment interested without resort to the video server. However, they have not considered the constraint of the server's upload bandwidth and the fairness between upload and download amounts at each peer. In this paper, we propose a novel P2P VoD streaming system, named peer cache adaptation (PECAN) where each peer adjusts its cache capacity adaptively to meet the server's upload bandwidth constraint and achieve the fairness. For doing so, we first propose a new cache replacement algorithm that designs the number of caches for a segment to be proportional to its popularity. Second, we mathematically prove that if the cache capacity of a peer is proportional to its segment request rate, the fairness between upload and download amounts at each peer can be achieved. Third, we propose a method that determines each peer's cache capacity adaptively according to the constraint of the server's upload bandwidth. Against the proposed design objective, some selfish peers may not follow our protocol to increase their payoff. To detect such peers, we design a simple distributed reputation and monitoring system. Through simulations, we show that PECAN meets the server upload bandwidth constraint, and achieves the fairness well at each peer. We finally verify that the control overhead in PECAN caused by the search, reputation, and monitoring systems is very small, which is an important factor for real deployment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.76-82
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• 2012

As the portable camcorder becomes popular, various video stabilization algorithms for de-shaking of camera motion have been developed. In the past, most video stabilization algorithms were based on 2-dimensional camera motion, but recent algorithms show much better performance by considering 3-dimensional camera motion. Among the previous video stabilization algorithms, 3D video stabilization algorithm using content-preserving warps is known as the state-of-the art owing to its superior performance. But, the major demerit of the algorithm is its high computational complexity. So, we present a computationally light full-frame warping algorithm based on ROI (region-of-interest) while providing comparable visual quality to the state-of-the art in terms of ROI. First, a proper ROI with a target depth is chosen for each frame, and full-frame warping based on the selected ROI is applied.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.89-96
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• 2016

This study analyzed with the case analysis of a series of processes from job analysis survey. And results analysis, and academic achievement in order to transform the curriculum of existing courses into the curriculum of NCS-based courses. Also this study analysed of the existing curriculum. Also analyzed the trend of workforce trends and needs of the broadcasting content industry. Through a needs analysis for the industry and alumni and students, video graphics, video editing and video directing were selected. In this paper, it dealt mainly with respect to the video graphics in a dual job. Modeling capability into the unit through a job analysis, animation, effects and lighting were chosen accordingly based introduction of 3D Graphics. Application of 3D Graphics were derived two courses and selected profiles and performance criteria. This training according to the NCS curriculum for students was evaluated based on the student's job was to investigate the learning ability. Academic achievement were the result satisfaction.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.43-50
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• 2009

We proposed similarity detection method of the video frame data that extracts the feature data of own video frame and creates the 1-D signal in this paper. We get the similar frame boundary and make the representative frames within the frame boundary to extract the similarity extraction between video. Representative frames make blurring frames and extract the feature data using DOG values. Finally, we convert the feature data into the 1-D signal and compare the contents similarity. The experimental results show that the proposed algorithm get over 0.9 similarity value against noise addition, rotation change, size change, frame delete, frame cutting.