• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.2
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• pp.53-61
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• 2011

This research presents an adaptive fast motion estimation (ME) computation on the stage of uneven multi-hexagon grid search (UMHGS) algorithm included in an unsymmetrical-cross multi-hexagon-grid search (UMHexagonS) in H.264 standard. The proposed adaptive method is based on statistical analysis and previously obtained motion vectors to reduce the computational complexity of ME. For this purpose, the algorithm is decomposed into three processes: skipping, terminating, and reducing search areas. Skipping and terminating are determined by the statistical analysis of the collected minimum SAD (sum of absolute difference) and the search area is constrained by the slope of previously obtained motion vectors. Simulation results show that 13%-23% of ME time can be reduced compared with UMHexagonS, while still maintaining a reasonable PSNR (peak signal-to-noise ratio) and average bitrates.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.183-188
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• 1994

A passivity-based adaptive controller for robots executing fine motion tasks is proposed. The robot dynamics is modelled such that it is subject to holonomic constraints and hence it can be treated as a particular case of constrained motion tasks. Energy-motivated stability analysis is used to conclude the asymptotic stability. Remarks regarding the structure of the controller are given. A computer simulations study is presented and a robust constraint stabilization algorithm is also proposed.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1361-1369
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• 1996

Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.11
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• pp.1156-1160
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• 2003

Many time-frequency analysis techniques have been used for motion compensated ISAR(Inverse Synthetic Aperture Radar) imaging. In this work, a novel time-frequency(T-F) analysis called evolutionary adaptive wavelet transform (EAWT) and evolutionary adaptive joint time-frequency(EAJTF) procedure are used for the motion compensated ISAR image. To show the validity of our algorism, we use simulated MIG-25 and Boeing 727(B-727) ISAR data. From the constructed ISAR image using EAWT and EAJTF, we show that our algorithm can obtain a clear motion compensated ISAR image such as other time-frequency analysis techniques.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.499-502
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• 1989

This paper is concerned with the stability analysis and the design of an auto pilot using direct model reference adaptive control for BTT missile with unknown dynamics when subjected to the longitudinal and lateral gusts. A motion of BTT missile can be separated into the longtudinal and lateral motione. The proposed algorithm is introduced different leakage terms about each motion into adaptation so as to prevent drift of the adaptive gain and alleviate gust effects and cross-coupling. The algorithm is applied to the 6DOF motion of an EMRAAT missile.

• Journal of Biomedical Engineering Research
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• v.28 no.3
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• pp.369-376
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• 2007

With the convergence of ubiquitous networking and medical technologies, ubiquitous healthcare(U-Healthcare) service has come in our life, which enables a patient to receive medical services at anytime and anywhere. In the u-Healthcare environment, intelligent real-time biosignal aquisition/analysis techniques are inevitable. In this study, we propose a motion artifact cancelation method in portable photoplethysmography(PPG) signal aquisition using an accelerometer and an adaptive filter. A preliminary experiment represented that the component of the pedestrian motion artifact can be found under 5Hz in the spectral analysis. Therefore, we collected PPG signals under both simulated conditions with a motor that generates circular motion with uniform velocity (from 1 to 5Hz) and a real walking condition. We then reduced the motion artifact using a recursive least square adaptive filter which takes the accelerometer output as a noise reference. The results showed that the adaptive filter can remove the motion artifact effectively and recover peak points in PPG signals, which represents our method can be useful to detect heart rate in real walking condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.43-44
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• 2006

The performance of the direct adaptive time-delay filter depends on the select time-delay. In this paper, the authors introduce a new scheme to adapt the time-delay which is to be used in conjunction with the direct adaptive command shaping for the improved vibration suppression in flexible motion system. In order to formulate the time-delay adaptation scheme, the authors have analyzed the effect of the time-delay value on the performance of the direct adaptive command shaping filter. By modifying the direct adaptation formula based on the analysis result the authors have established a set of equations to adapt the time-delay toward the optimal value. Simulation results show the effectiveness of the proposed time-delay adaptation approach for the improved vibration suppression.