• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.801-808
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• 2007

Video coding standards such as MPEG-2, MPEG-4, H.263, and H.264 transmit a compressed video data using wired/wireless communication line with limited bandwidth. Because highly compressed bit-streams is likely to fragile to error from channel noise, video is damaged by error. There have been many research works on error concealment techniques, which recover transmission errors at decoder side [1, 2]. We designed an error concealment technique for lost motion vectors of H.264 video coding. In this paper, we propose a Kalman filter based motion vector recovery scheme, and experimented with standard video sequences. The experimental results show that our scheme restores original motion vector with more precision of 0.91 - 1.12 on average over conventional H.264 decoding with no error recovery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.1036-1043
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• 2005

In this paper, we propose a sequential motion vector recovery algorithm for H.264 video coding standard. Motion vectors of H.264 video coding standard cover relatively smaller areas than other standard, since motion estimation of H.264 takes place in the fashion of variable block size. Therefore, the correlation of motion vectors between neighboring blocks increases as the block size of motion estimation is lowered. Under the framework of sequential recovery, we introduce a motion vector recovery using $\alpha$-trimed mean filter. Experimental results show that proposed algorithm is useful in real time video delivery .with nearly comparable or better visual quality than previous approaches such as macro block boundary matching and Lagrage interpolation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.148-155
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• 2006

For the improvement of coding efficiency, the H.264 standard uses new coding tools which are not used in previous coding standards. Among new coding tools, motion estimation using smaller block sizes leads to higher correlation between the motion vectors of neighboring blocks. This characteristic of H.264 is useful for the motion vector recovery. In this paper, we propose the motion vector recovery method based on optical flow. Since the proposed method estimates the optical flow velocity vector from more accurate initial value and optical flow region is limited to 16$\times$16 block size, we can alleviate the complexity of computation of optical flow velocity. Simulation results show that our proposed method gives higher objective and subjective video quality than previous methods.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.161-163
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• 2005

In this paper, we propose an efficient motion vector recovery algorithm for the new coding standard H.264, which makes use of the Lagrange interpolation formula. In H.264/AVC, a 16$\times$16 macroblock can be divided into different block shapes for motion estimation, and each block has its own motion vector. In the natural video the motion vector is likely to move in the same direction, hence the neighboring motion vectors are correlative. Because the motion vector in H.264 covers smaller area than previous coding standards, the correlation between neighboring motion vectors increases. We can use the Lagrange interpolation formula to constitute a polynomial that describes the motion tendency of motion vectors, and use this polynomial to recover the lost motion vector. The simulation result shows that our algorithm can efficiently improve the visual quality of the corrupted video.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.630-640
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• 2002

The compressed video bitstream is very sensitive to transmission errors. If we lost packet or received with errors during the transmission, not only the current frame will be corrupted, but also errors will propagate to succeeding frames. Error concealment is a data recovery technique that enables the decoder to conceal effects of transmission errors by predicting the lost or corrupted video data from the previously reconstructed error free information. Motion vection recovery and motion compensation with the estimated motion vector is a good approach to conceal the corrupted macroblock data. In this paper, we prove that it is reasonable to use the estimated motion vector to conceal the lost macroblock by providing macroblock distortion models. After we propose a new motion vector recovery algorithm based on optical flow fields, we compare its performance to those of conventional error concealment methods. The proposed algorithm has smaller computational complexity than those of conventional algorithms.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.65-74
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• 2006

The MPEG-2 video compressed bitstream is very sensitive to transmission errors due to the complex coding structure of the MPEG-2 video coding standard. If one packet is lost or received with errors, not only the current frame will be corrupted, but also errors will propagate to succeeding frames within a group of pictures. Therefore, we employ various error resilient coding/decoding techniques to protect and reduce the transmission error effects. Error concealment technique is one of them. Error concealment technique exploits spatial and temporal redundancies of the correctly received video data to conceal the corrupted video data. Motion vector recovery and compensation with the estimated motion vector is good approach to conceal the corrupted data. In this paper, we propose various error concealment algorithms based on motion vector recovery, and compare their performance to those of conventional error concealment methods.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.1
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• pp.16-21
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• 2015

Most video services are transmitted in wireless networks. In a network environment, a packet of video is likely to be lost during transmission. For this reason, numerous error concealment (EC) algorithms have been proposed to combat channel errors. On the other hand, most existing algorithms cannot conceal the whole missing frame effectively. To resolve this problem, this paper proposes a new Adaptive Prediction Unit-based Motion Vector Extrapolation (APMVE) algorithm to restore the entire missing frame encoded by High Efficiency Video Coding (HEVC). In each missing HEVC frame, it uses the prediction unit (PU) information of the previous frame to adaptively decide the size of a basic unit for error concealment and to provide a more accurate estimation for the motion vector in that basic unit than can be achieved by any other conventional method. The simulation results showed that it is highly effective and significantly outperforms other existing frame recovery methods in terms of both objective and subjective quality.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.29-37
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• 2008

To transmit video bit stream over low bandwidth such as wireless channel, high compression algorithm like H.264 codec is exploited. In transmitting high compressed video bit-stream over low bandwidth, packet loss causes severe degradation in image quality. In this paper, a new algorithm for recovery of missing or erroneous motion vector is proposed. Considering that the missing or erroneous motion vectors in blocks are closely correlated with those of neighboring blocks. Motion vector of neighboring blocks are clustered according to average linkage algorithm clustering and a representative value for each cluster is determined to obtain the candidate motion vector sets. As a result, simulation results show that the proposed method dramatically improves processing time compared to existing H.264/AVC. Also the proposed method is similar to existing H.264/AVC in terms of visual quality.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.77-86
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• 1996

In this paper we deal with the problem of recovering 3-D motion and structure from a time-varying 2-D velocity vector field. A great deal has been done on this topic, most of which has concentrated on finding necessary and sufficient conditions for there to be a unique 3-D solution corresponding to a given 2-D motion. While previous work provides useful theoretical insight, in most situations the known algorithms have turned out to be too sensitive to be of much practical use. It appears that any robust algorithm must improve the 3-D solutions over time. As a step toward such algorithm, we present a method for recovering 3-D motion and structure from a given time-varying 2-D velocity vector field. The surface of the object in the scene is assumed to be locally planar. It is also assumed that 3-D velocity vectors are piecewise constant over three consecutive frames (or two snapshots of flow field). Our formulation relates 3-D motion and object geometry with the optical flow vector as well as its spatial and temporal derivatives. The linearization parameters, or equivalently, the first-order flow approximation (in space and time) is sufficient to recover rigid body motion and local surface structure from the local instantaneous flow field. We also demonstrate, through a sensitivity analysis carried out for synthetic and natural motions in space, that 3-D motion can be recovered reliably.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2371-2374
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• 2003

In transmitting compressed video bit-stream over Internet, packet loss causes error propagation in both spatial and temporal domain, which in turn leads to severe degradation in image qualify In this paper, a new approach for the recovery of lost or erroneous Motion Vector(MV)s by clustering the movements of neighboring blocks by their homogeneity is proposed. MVs of neighboring blocks are clustered according to ALA(Average Linkage Algorithm) clustering and a representative value for each cluster is determined to obtain the candidate MV set. By computing the distortion of the candidates, a MV with the minimum distortion is selected. Experimental results show that the proposed algorithm exhibits better performance in many cases than existing methods.