• Journal of Digital Convergence
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• v.10 no.6
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• pp.197-203
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• 2012

In this paper, researching for the video quality estimation of IPTV in the situation that increase the broadcasting network traffic on the IPTV multicasting service using the ETSI TR 101 290 that is the European digital video quality standard estimating method and present the experiment result. Proving that the intimate relation is between IPTV video quality and ETSI TR 101 290 estimation, also ETSI TR 101 290 can detect the video quality factors which can't be detected by the exist video estimation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.308-324
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• 2018

HTTP adaptive streaming (HAS) is a promising technology for delivering video content over the Internet. HAS-based video streaming solutions rely on bandwidth estimation to select the appropriate video bitrate. Video streaming solutions that consider network conditions provide users with seamless video playback. However, when multiple clients compete for a common bottleneck link, conventional bandwidth estimation schemes that consider only one client overestimate the network bandwidth due to the ON-OFF traffic pattern. The bandwidth overestimation can cause Quality of Experience (QoE) degradation, such as unnecessary changes in video quality, and unfairness of video quality. In this paper, we propose a client-side bandwidth estimation scheme to obtain a better QoE of HAS in the multiple-client environment. The proposed scheme differentiates the client buffer status according to the buffer occupancy, and then estimates the available network bandwidth based on the buffer status and segment throughput. We evaluate the performance of HAS implemented in the ns-3 network simulator. Simulation results show that compared with the conventional schemes, the proposed scheme can enhance the QoE.

• Journal of Web Engineering
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• v.20 no.8
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• pp.2413-2432
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• 2021

Recently, the demand for high-quality video content has rapidly been increasing, led by the development of network technology and the growth in video streaming platforms. In particular, displays with a high refresh rate, such as 120 Hz, have become popular. However, the visual quality is only enhanced if the video stream is produced at the same high frame rate. For the high quality, conventional videos with a low frame rate should be converted into a high frame rate in real time. This paper introduces a bidirectional intermediate flow estimation method for real-time video frame interpolation. A bidirectional intermediate optical flow is directly estimated to predict an accurate intermediate frame. For real-time processing, multiple frames are interpolated with a single intermediate optical flow and parts of the network are implemented in 16-bit floating-point precision. Perceptual loss is also applied to improve the cognitive performance of the interpolated frames. The experimental results showed a high prediction accuracy of 35.54 dB on the Vimeo90K triplet benchmark dataset. The interpolation speed of 84 fps was achieved for 480p resolution.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1131-1141
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• 2018

Motion Estimation which is used to reduce the redundant data plays an important role in video compressions. However, it requires huge computational complexity of the encoder part. And therefore many fast motion estimation methods has been developed to reduce complexity. Multi-view video is obtained by using many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed a fast motion estimation method for multi-view video. The proposed method predicts a search start point by using correlated candidate vectors of the current block. According to the motion size of the start search point, a search start pattern of the current block is decided adaptively. The proposed method proves to be about 2 ~ 5 times faster than existing methods while maintaining similar image quality and bitrates.

• ETRI Journal
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• v.43 no.3
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• pp.538-548
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• 2021

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.

• Journal of Broadcast Engineering
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• v.3 no.1
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• pp.69-84
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• 1998

In digital broadcasting, services such as digital satellite TV, cable TV and digital terrestrial TV, several video programs are compressed by MPEG-2, and then simultaneously transmitted over a conventional CBR (Constant Bit Rate) broadcasting channel. In this paper, we propose a joint quality control scheme to be able to accurately control the relative picture quality among the video programs, which is achieved by simdt;,nL'Ously controlling the video encoders to generate the VBR (Variable Bit Rate) compressed video streams. Our quality control scheme can prevent the video buffer overflow and underflow by total target bit allocation process, and also exactly control the relative picture quality in terms of PSNR (Peak Signal to Noise Ratio) between some programs requiring higher picture quality and others by rate-distortion modification. Furthermore we present a rate-distortion estimation method for MPEG-2 video, which is base of our joint quality control, and verify its performance by experiments. The most attractive features of this estimation method are as follows: 1) computational complexity is low because main operation for the estimation is to calculate the histogram of OCT coefficients into quantizer; 2) estimation results are very accurate enough to be applied to the practical MPEG-2 video coding applications. Simulation results show that the proposed joint quality control scheme accurately controls the relative picture quality among the video progran1s transmitted over a single channel as well as provides more consistent and higher picture quality than independent coding scheme that encodes each program independently.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1205-1215
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• 2015

Efficient multi-view coding techniques are needed to reduce the complexity of multi-view video which increases in proportion to the number of cameras. To reduce the complexity and maintain image quality and bit-rates, an motion estimation method and temporal prediction structure are proposed in this paper. The proposed motion estimation method exploits the characteristic of motion vector distribution and the motion direction and motion size of the block to place search points and decide the search patten adaptively. And the proposed prediction structure divides every GOP to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experiment results show that the complexity reduction of the proposed temporal prediction structure and motion estimation method over hierarchical B pictures prediction structure and TZ search method which are used in JMVC(Joint Multi-view Video Coding) reference model can be up to 45∼70% while maintaining similar video quality and bit rates.

• ETRI Journal
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• v.44 no.1
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• pp.38-50
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• 2022

This paper presents a study on the use of encoder-derived features in decoder-side depth estimation. The scheme of multiview video encoding does not require the transmission of depth maps (which carry the geometry of a three-dimensional scene) as only a set of input views and their parameters are compressed and packed into the bitstream, with a set of features that could make it easier to estimate geometry in the decoder. The paper proposes novel recursive block splitting for the feature extraction process and evaluates different scenarios of feature-driven decoder-side depth estimation, performed by assessing their influence on the bitrate of metadata, quality of the reconstructed video, and time of depth estimation. As efficient encoding of multiview sequences became one of the main scopes of the video encoding community, the experimental results are based on the "geometry absent" profile from the incoming MPEG Immersive video standard. The results show that the quality of synthesized views using the proposed recursive block splitting outperforms that of the state-of-the-art approach.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.329-336
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• 2017

In video compression, Motion Estimation(ME) limits the performance of image quality and generated bit rates. However, it requires much complexity in the encoder part. Multi-view video uses many cameras at different positions. Multi-view video coding needs huge computational complexity in proportion to the number of the cameras. To reduce computational complexity and maintain the image quality, an effective motion estimation method is proposed in this paper. The proposed method exploiting the characteristics of motion vector distribution and the motion of video. The proposed is a kind of a hierarchical search strategy. This strategy consists of multi-grid rhombus pattern, diagonal pattern, rectangle pattern, and refinement pattern. Experiment results show that the complexity reduction of the proposed method over TZ search method and PBS (Pel Block Search) on JMVC (Joint Multiview Video Coding) can be up to 40~75% and 98% respectively while maintaining similar video image quality and generated bit rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.497-504
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• 2005

We propose an efficient video watermarking scheme using re-estimation and minimum modification technique of motion vectors. Conventional methods based on motion vectors do watermarking using modification of motion vectors. However, change of motion vectors results in the degradation of video quality. Thus, our scheme minimizes the modification of the original motion vectors and replaces an original motion vector by the adjacent optimal motion vector using re-estimation of motion vectors to avoid degradation of video quality. Besides, our scheme guarantees the amount of embedded watermark data using the adaptive threshold considering for an efficient video watermarking. In addition, this is compatible with current video compression standards without changing the bitstream. Experimental result shows that the proposed scheme obtains better video quality than other previous algorithms by about $0.6{\sim}1.3\;dB$.