• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.371-374
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• 2001

본 논문에서는 움직임 보상을 이용한 Motion-Adaptive De-interlacing Method를 제안 한다. 정확한 움직임 추정을 위해서 Pre-filter로서 EBMF(Edge Based Median Filter)를 사용하며 새로운 Block Matching Method를 제안한다. Temporal Filter로서 Motion Missing Error를 제거하기 위해 입력 영상의 움직임 영역에 따라 각각 다른 임계 값을 적용하는 AMPDF(Adaptive Minimum Pixel Difference Filter)를 적용하였으며 MMD(Maximum Motion Detection)와 SAD(Sum of Difference)를 이용하여 빠른 움직임 영역에서 화질을 향상시켰다. 최종적으로 잘못된 움직임 보상에 기인하는 화질의 열화를 방지하기 위한 Motion Correction Filter를 제안한다.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.955-958
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• 1998

This paper describes the algorithm which extracts moving vehicles from sequential images and tracks those vehicles using Kalman filter. This work is composed of a motion segmentation stage which extracts moving objects from sequential images and gets features of objects, and a motion estimation stage which estimates the position and the motion of moving objects using Kalman filter. In the motion estimation stage, applying to affine motion model we divided the Kalman filter into position filter and velocity filter to employ linear Kalman filter. Multi-target tracking requires a data association component that decides which measurement to use for updating the state of which object. We use pattern recognition method to solve this problem.

• Journal of Mechanical Science and Technology
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• v.17 no.2
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• pp.221-229
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• 2003

In the virtual environment, reality can be enhanced by offering the motion based on a motion simulator in harmony with visual and auditory modalities. In this research the Stewart-Gough-platform-based motion simulator has been developed. Implementation of vehicle dynamics is necessary in the motion simulator for realistic sense of motion, so bicycle dynamics is adopted in this research. In order to compensate for the limited range of the motion simulator compared with the real vehicle motion, washout algorithm composed of high-pass filter, low-pass filter and tilt coordination is usually employed. Generally, the washout algorithm is used with fixed parameters. In this research a new approach is proposed to tune the filter parameters based on fuzzy logic in real-time. The cutoff frequencies of the filters are adjusted according to the workspace margins and driving conditions. It is shown that the washout filter with the fuzzy-based parameters presents better performance than that with the fixed ones.

• Journal of Internet Computing and Services
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• v.4 no.2
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• pp.31-37
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• 2003

Recently, motion capture has become one of the most promising technologies in animation. Realistic motion data can be captured by recording the movement of a real actor with an optical or magnetic motion capture system. This paper deals with motion editing by a geometric mean filter. Since the captured motion has some noises that cause a jerky motion, it needs a smoothing process to make it natural. A geometric mean filter is proposed to produce natural motions without jerky motions. Experimental results show that the geometric mean filter can effectively remove noises that cause a jerky motion and it can guarantee the most natural motions among various spatial filters. This method could be applied to the various fields such as real time animation, virtual reality applications, 3D applications, and etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

• Journal of Korea Multimedia Society
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• v.21 no.9
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• pp.1052-1061
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• 2018

In this paper, we propose a new algorithm that is robust against the effects of objects that are relatively unaffected by camera motion and can accurately detect camera motion even in high resolution images. First, for more accurate camera motion detection, a global motion filter based on entropy of a motion vector is used to distinguish the background and the object. A block matching algorithm is used to find exact motion vectors. In addition, a matched filter with the angle of the ideal motion vector of each block is used. Motion vectors including 4 kinds of diagonal direction, zoom in, and zoom out are added additionally. The experiment shows that the precision, recall, and accuracy of camera motion detection compared to the recent results is improved by 12.5%, 8.6% and 9.5%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.986-991
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• 2014

The PPG signal used in mobile-healthcare and telemedicine system is including the various motion artifact that is signal generated from patient's movements. Recently, although the various methods to remove motion artifacts have been suggested, the performances of these methods are still not satisfactory. Therefore, this s study suggested the novel method based on the Kalman filter and adaptive filter to remove motion artifacts, and we used various motion artifacts to analyze the performance of the proposed method. In the results of experiments, the signal-to-noise ratio of proposed method showed good performace that was 4.8 times of moving average filter.

• Journal of the Korean Mathematical Society
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• v.55 no.5
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• pp.1063-1073
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• 2018

We study the estimation of the drift parameter and the change point obtained through a Kalman-Bucy filter for linear systems with signal driven by a fractional Brownian motion and the observation driven by a Brownian motion.

• Journal of the Korea Computer Graphics Society
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• v.4 no.1
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• pp.21-29
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• 1998

This paper deals with character animation using motion capture. The captured motion requires the editing process to smooth the jerky motion by the sensor noise, or to combine several clip-motion libraries. For this purpose, we describe a simple technique for editing the captured motion using the Kalman filter technique. Our formulation allows the generated motion to satisfy the kinematic constraints of the human model. Furthermore, it provides us with a multi-level control mechanism of the motion resolution by changing the uncertainty of the measurement model and the seamless motion transition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.