• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.108-116
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• 1994

In this paper, we propose a new motion vector smoothing scheme which has high reliability and coding efficiency of motion vectors. In motion vector filed, groupings are made using angle and magnitude of the motion vectors. In each group, the unreliable motion vectors are corrected by the motion vector smoothing. In 3$\times$3 window, motion vector of the current block is made to group, and the motion vector smoothing is performed only in that group. Result of computer simulation shows much improvement of the reliability of motion vectors. Moreover, coding bits of the motion vector are diminished from 0.967 to 6.773 bits per block.

• Smart Media Journal
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• v.6 no.2
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• pp.9-14
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• 2017

A packet loss in wireless environments causes a severe degradation of video quality in video communications. In this paper, a novel video error concealment algorithm is presented by combining boundary errors and a block reliability measure. The block reliability measure decides the reliability of a block by checking residual errors of a block. In the proposed approach, a motion vector of a missing unreliable block in an inter coded frame is obtained initially based on the motion vector of the same block in the reference frame. Furthermore, if the block in the reference frame is unreliable according to the reliability measure, a new motion vector is decided based on block boundary errors around the initial motion vector. According to our simulations, the proposed approach shows promising results for error concealment in error-prone wireless environments.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.103-110
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• 2011

In this paper, an adaptive motion vector smoothing scheme based on weighted vector median filtering is proposed in order to eliminate the motion outliers more effectively for improving the quality of side information in frame-based distributed video coding. We use a simple motion vector outlier reliability measure for each block in a motion compensated interpolated frame and apply weighted vector median filtering only to the blocks with unreliable motion vectors. Simulation results show that the proposed adaptive motion vector smoothing algorithm improves the quality of the side information significantly while maintaining low complexity at the encoder in frame-based distributed video coding.

• ETRI Journal
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• v.33 no.2
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• pp.295-298
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• 2011

We propose a motion-compensated frame interpolation method in which an accurate backward/forward motion vector pair (MVP) is estimated based on a parabolic motion model. A reliability measure for an MVP is also proposed to select the most reliable MVP for each interpolated block. The possibility of deformation of bidirectional corresponding blocks is estimated from the selected MVP. Then, each interpolated block is produced by combining corresponding blocks with the weights based on the possibility of deformation. Experimental results show that the proposed method improves PSNR performance by up to 2.8 dB as compared to conventional methods and achieves higher visual quality without annoying blockiness artifacts.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.237-247
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• 2003

The Motion Estimation (ME) process is an important part of a video encoding systems since they can significantly reduce bitrate with keeping the output quality of an encoded sequence. Unfortunately this process may dominate the encoding time using straightforward full search algorithm (FS). Up to now, many fast algorithms can reduce the computation complexity by limiting the number of searching locations. This is accomplished at the expense of less accuracy of motion estimation. In this paper, we introduce a new fast motion estimation method based on the spatio-temporal correlation of adjacent blocks. A reliable predicted motion vector (RPMV) is defined. The reliability of RPMV is shown on the basis of motion vectors achieved by FS. The scalar and the direction of RPMV are used in our proposed scheme. The experimental results show that the proposed method Is about l1~14% faster than the nearest neighbor method which is a wellknown conventional fast scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.102-111
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• 2009

In this paper, we propose a de-interlacing algorithm that combines a motion compensation (MC) method and the vertical-temporal filter with motion compensation (MC V-T filter) according to motion compensation reliability. The MC method represent one of the best ways of improving the resolution of de-interlaced frames, but it may introduce motion compensation artifacts in regions with incorrect motion information. In these regions, the MC V-T filter that is very robust to motion vector errors can be used to correct motion compensation artifacts. The combination between two methods is controlled by the motion compensation reliability that is measured by analyzing the estimated motion vectors and the results of MC. The motion compensation reliability contains information about motion compensation artifacts of MC results and determines the combination weight according to this information. Therefore, the combination rule of the proposed method is more accurate than those of the conventional methods and it enables the proposed method to provide high quality video sequences without producing any visible artifacts. Experimental results with various test sequences show that the proposed algorithm outperforms conventional algorithms in terms of both visual and numerical criteria.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.74-86
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• 2006

This paper proposes a robust and computationally efficient algorithm for automatic video object segmentation. For implementing the spatio-temporal segmentation, which aims for efficient combination of the motion segmentation and the color segmentation, an SOM-based hierarchical clustering method in which the segmentation process is regarded as clustering of feature vectors is employed. As results, problems of high computational complexity which required for obtaining exact segmentation results in conventional video object segmentation methods, and the performance degradation due to noise are significantly reduced. A measure of motion vector reliability which employs MRF-based MAP estimation scheme has been introduced to minimize the influence from the motion estimation error. In addition, a noise elimination scheme based on the motion reliability histogram and a clustering validity index for automatically identifying the number of objects in the scene have been applied. A cross projection method for effective object tracking and a dynamic memory to maintain temporal coherency have been introduced as well. A set of experiments has been conducted over several video sequences to evaluate the proposed algorithm, and the efficiency in terms of computational complexity, robustness from noise, and higher segmentation accuracy of the proposed algorithm have been proved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8C
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• pp.824-831
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• 2005

In the reconstruction of high resolution (HR) images from low resolution (LR) images frames, the error in the estimated motion degrades the reliability of the reconstructed HR image. Some methods were recently proposed where motion estimation and HR reconstruction is performed simultaneously. The estimated motion is still prone to error when it is based on a simple block matching. In this paper, we propose a reconstruction of a HR image by applying POCS and a regularized block matching simultaneously. In this method, a motion vector is obtained from a regularized block matching algorithm since the motion of a pixel in an image is highly correlated with the motion in neighboring regions. Experimental results show that the improved accuracy of the estimated motion vectors results in higher PSNR of the reconstructed HR images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.867-869
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• 2012

FRUC(Frame Rate Up Conversion) is core techniques for higher quality terminals or low channel rate. For these applications, in this paper, we propose a block-based reliability evaluation method for FRUC techniques using bi-lateral symmetrical motion estimation. First, in order to measure the reliability, by introducing cost evaluation tools such as motion vector consistency as well as temporal matching and spatial matching characteristics and then by combining these tools, we propose an efficient method which arrange the blocks according to distortion size. Through several simulations, it is shown that the proposed method is very effective in finding the high distortion blocks. Furthermore, it is expected that the proposed method can be effectively utilized in FRUC techniques and Distributed Video Coding technologies.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.