• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.949-955
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• 2005

In this Paper, we propose fast block matching algorithm by dividing complex areas based on complexity order of reference block and square sub-block to reduce an amount of computation of full starch(FS) algorithm for fast motion estimation, while keeping the same prediction quality compared with the full search algorithm. By using the fact that matching error is proportional to the gradient of reference block, we reduced unnecessary computations with square sub-block adaptive matching scan based image complexity instead of conventional sequential matching scan and row/column based matching scan. Our algorithm reduces about $30\%$ of computations for block matching error compared with the conventional partial distortion elimination(PDE) algorithm without any prediction quality, and our algorithm will be useful in real-time video coding applications using MPEG-4 AVC or MPEG-2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.712-719
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• 2008

Temporal error concealment indicates the algorithm that restores the lost video data using temporal correlation between previous frame and current frame with lost data. It can be categorized into the methods of block-based and pixel-based concealment. The proposed method in this paper is for pixel-based temporal error concealment using affine transform. It outperforms especially when the object or background in lost block has geometric transform which can be modeled using affine transform, that is, rotation, magnification, reduction, etc. Furthermore, in order to maintain good performance even though one or more motion vector represents the motion of different objects, we defines a cost function. According to cost from the cost function, the proposed method adopts affine error concealment adaptively. Simulation results show that the proposed method yields better performance up to 1.9 dB than the method embedded in reference software of H.264/AVC.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.823-835
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• 2006

Multimedia is a very popular service in the Internet. But, we cannot provide multimedia service at a uniform content, because networks and devices are various. Thus, an adaptive service is needed for multimedia transmission. Video Transcoding is the good solution that can service multimedia adaptively. This paper proposes the streaming system that is composed of encoder, transcoder, decoder The encoder enhanced time complexity and PSNR in case of transcoding using PP(Prediction Period). The decoder is almost same as the traditional media player. Transcoder reduced time complexity through combination of prediction period in encoder and skipping period to control frame rate in transcoder. In simulation results, the performances of proposed scheme outperform the system with traditional transcoder in time complexity and PSNR.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.55-63
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• 2011

This paper describes new moving target detection technique combining two algorithms to detect targets and reject clutters in video frame images for surveillance system: One obtains the region of moving target using phase correlation method using $N{\times}M$ sub-block images in frequency domain. The other uses adaptive threshold using learning weight for extracting target candidates in subtracted image. The block region with moving target can be obtained using the characteristics that the highest value of phase correlation depends on the movement of largest image in block. This technique can be used in camera motion environment calculating and compensating camera movement using FFT phase correlation between input video frame images. The experimental results show that the proposed algorithm accurately detects target(s) with a low false alarm rate in variety environment using the receiver operating characteristics (ROC) curve.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2326-2333
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• 2009

In the adaptable bandwidth allocation technique, a transmission plan for variable rate video data is made by smoothing algorithms such as CBA algorithm and the data is sent by the transmission plan considering network traffic. But the CBA algorithm, the MCBA algorithm, MVBA algorithm and the other smoothing algorithms produce a transmission plan where the size of the increasing interval of transmission rate is generally larger than the size of the decreasing interval. And the transmission rate in CBA algorithm, the MCBA algorithm, the MVBA algorithm is changed in overflow curve during the increasing interval of transmission rate. This may cause many frames to be discarded when available transmission rate is larger than transmission rate by the transmission plan. In this paper, the smoothing algorithm, where transmission rate is changed in the middle of underflow curve and overflow curve to decrease the number of discarded frames, but the transmission rate increases at the minimum, and the CBA algorithm, the MCBA algorithm, the MVBA algorithm are applied to a transmission plan in the adaptable bandwidth allocation technique, and the minimum frame rates, the average frame rates, the variation of frame rates, and the numbers of discarded frames are compared in among algorithms.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.813-823
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• 2018

UHD content is characterized by higher bandwidth requirements to provide seamless playback. The existing HTTP adaptive streaming scheme periodically requests video segment of lower quality than the available bandwidth in the steady state. In the steady state, the On-Off pattern is repeated due to the difference of the available bandwidth and the encoding rate of the content. And the repeated Off interval is causing the problem that can not efficiently use the available bandwidth. In the wireless environment where the delay and loss rate are higher with large bandwidth fluctuations, this problem is exacerbated because the available bandwidth is estimated inaccurately. Therefore, in this paper, we propose a segment scheduling scheme for efficient bandwidth utilization of UHD contents streaming in wireless environment. Proposed scheme is a group segment that simultaneously reqeusts multiple segments in one request message in order to reduce frequency of OFF interval. Through simulation, Our scheme improves bandwidth utilization.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.32-43
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• 2010

This paper presents deblocking filter for low-complexity video decoder. Baseline profile of the H.264/AVC used for mobile devices such as mobile phones has two times higher compression performance than the MPEG-4 Visual but it has a problem of serious complexity as using 1/4-pel interpolation filter, adaptive entropy model and deblocking filter. This paper presents low-complexity deblocking filter for decreasing complexity of decoder with preserving the coding efficiency of the H.264/AVC. In this paper, the proposed low-complexity deblocking filter decreased 49% of branch instruction than conventional approach as calculating value of BS by using the CBP. In addition, a range of filtering of strong filter applied in intra macroblock boundaries was limited to two pixels. According to the experimental results, the proposed low-complexity deblocking filter decreased -0.02% of the BDBitrate comparison with baseline profile of the H.264/AVC, decreased 42% of the complexity of deblocking filter, and decreased 8.96% of the complexity of decoder.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.618-631
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• 2017

In this paper, we propose a modification of fuzzy logic based DASH adaptation algorithm(FDASH) for seamless media service in time-varying network conditions. The proposed algorithm selects more appropriate bit-rate for the next segment by the modification of the Fuzzy Logic Controller(FLC) and reduces the number of video bit-rate changes by applying Segment Bit-rate Filtering Module(SBFM). Also, we apply the Start Mechanism for clients not to watch the low quality videos in the very beginning stage of streaming service and add the Sleeping Mechanism to avoid any buffer overflow expected. Ultimately, we verified by using NS-3 Network Simulator that the proposed method shows better performance compared to FDASH. According to the experimental results, there is no buffer underflow/overflow within the limited buffer size, which is not guaranteed in FDASH on the other hand. Also, we confirmed that mFDASH has almost the same level of average video quality against FDASH and reduces about 50% of number of video bit-rate changes compared to FDASH in Point-to-Point network and Wi-Fi network.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.660-673
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• 2001

In Video-on-Demand (VoD) servers, disk throughput is an important system design parameter because it is directly related to the number of user requests that can be served simultaneously. In this paper, we propose an efficient periodic request grouping scheme for disk array-based VoD servers that reduces the disk seek time, thus improving the disk throughput of VoD disk arrays. To reduce the disk seek time, the proposed scheme groups the periodic requests that access data blocks stored in adjacent regions into one, and arranges these groups in a pre-determined order (e.g., in left-symmetric or right-symmetric fashion). Our simulation result shows that the proposed scheme reduces the average disk bandwidth required by a single video stream and can serve more user requests than existing schemes. For a data block size of 192KB, the number of simultaneously served user requests is increased by 8% while the average waiting time for a user request is decreased by 20%. We also propose an adaptation technique that conforms the proposed scheme to the user preference changes for video streams.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.385-394
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• 2009

Face tracking and recognition are difficult problems because the face is a non-rigid object. The main reasons for the failure to track and recognize the faces are the changes of a face pose and environmental illumination. To solve these problems, we propose a nonlinear manifold framework for the face pose and the face illumination normalization processing. Specifically, to track and recognize a face on the video that has various pose variations, we approximate a face pose density to single Gaussian density by PCA(Principle Component Analysis) using images sampled from training video sequences and then construct the GMM(Gaussian Mixture Model) for each person. To solve the illumination problem for the face tracking and recognition, we decompose the face images into the reflectance and the illuminance using the SSR(Single Scale Retinex) model. To obtain the normalized reflectance, the reflectance is rescaled by histogram equalization on the defined range. We newly approximate the illuminance by the trained manifold since the illuminance has almost variations by illumination. By combining these two features into our manifold framework, we derived the efficient face tracking and recognition results on indoor and outdoor video. To improve the video based tracking results, we update the weights of each face pose density at each frame by the tracking result at the previous frame using EM algorithm. Our experimental results show that our method is more efficient than other methods.