• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1997년도 추계학술대회논문집; 한국과학기술회관; 6 Nov. 1997
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• pp.154-159
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• 1997

In this paper, we describe the OGY method that convert the motion on a chaotic attractor to attracting time periodic motion by malting only small perturbations of a control parameter. The OGY method is illustrated by application to the control of the chaotic motion in chaotic attractor to happen at the famous Logistic map and Henon map and confirm it by making periodic motion. We apply it the chaotic motion at the behavior of the thin beam under periodic torsional base-excitation, and this chaotic motion is made the periodic motion by numerical experiment in the time evaluation on this chaotic motion. We apply the OGY method with the Jacobian matrix to control the chaotic motion to the periodic motion.

• IEIE Transactions on Smart Processing and Computing
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• 제5권5호
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.74-79
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• 2005

In this paper, we propose a novel approach to decentralized motion planning and conflict-resolution for multiple mobile agents working in an environment with unexpected moving obstacles. Our proposed motion planner has two characteristics. One is a real-time collision prognosis based on modified collision map. Collision map is a famous centralized motion planner with low computation load, and the collision prognosis hands over these characteristics. And the collision prognosis is based on current robots status, maximum robot speeds, maximum robot accelerations, and path information produced from off-line path planning procedure, so it is applicable to motion planner for multiple agents in a dynamic environment. The other characteristic is that motion controller architecture is based on potential field method, which is capable of integrating robot guidance to the goals with collision avoidance. For the architecture, we define virtual obstacles making delay time for collision avoidance from the real-time collision prognosis. Finally the results obtained from realistic simulation of a multi-robot environment with unknown moving obstacles demonstrate safety and efficiency of the proposed method.

• 한국콘텐츠학회논문지
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• 제10권4호
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• pp.28-35
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• 2010

다중 참조 영상을 이용한 가변 블록 크기의 움직임 예측 및 보상 기법이 부호화 효율을 높이기 위해 H.264/AVC에 채택되었다. 하지만 움직임 예측 및 보상으로 인한 계산량은 다중 참조 영상과 가변 블록의 수에 비례하여 증가한다. 본 논문에서는 화질은 유지하며 계산량을 줄이기 위한 새로운 고속 참조 영상선택 방법을 제안한다. 먼저 다중 참조 영상들에 대해서 $4{\times}4$ 블록의 SAD값을 이용하여 움직임 벡터 참조 지도를 만든다. 다음으로 가변 블록 크기의 움직임 예측 및 보상이 움직임 벡터 참조 지도를 활용하여 실시된다. 제안하는 방법은 H.264/AVC 표준과 비교하여 BDPSNR은 평균적으로 0.01dB 나빠지고 BDBR은 약 0.27% 증가하지만 영상 부호화 속도를 약 38% 단축시킨다.

• 방송공학회논문지
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• 제23권1호
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• pp.3-10
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• 2018

깊이맵은 현재 다양한 분야에서 활용되고 있다. 이러한 깊이맵을 인공 신경망으로 생성하는 연구가 최근 관심을 받고 있다. 본 논문에서는 기존의 기 제작된 깊이맵 생성 알고리즘을 합성곱 신경망으로 구현할 수 있는지에 대한 타당성을 검증한다. 먼저 깊이맵은 관심맵과 운동 히스토리 영상의 가중치 합으로 얻는다. 실험영상과 깊이맵을 합성곱 신경망의 입력과 출력으로 하여, 신경망을 학습시킨다. 정성적, 정량적 실험 결과는 제안한 합성곱 신경망이 깊이맵 생성 방법을 대체할 수 있다는 것을 보여준다.

• 방송공학회논문지
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• 제20권4호
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• pp.557-567
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• 2015

정지영상에서 공간 관심맵을 생성하는 다양한 방법들이 소개되어 왔고, 최근에는 동영상의 운동정보를 활용하는 운동 관심맵 예측 기법이 활발히 연구되고 있다. 운동 관심맵은 운동정보 및 영역분할을 활용하고 있지만, 일반적인 영상에서는 만족스러운 데이터를 얻는 것은 어려움이 존재한다. 또한 우수한 관심맵을 얻기 위해서는 객체 운동, 카메라 운동 등의 운동유형 정보가 필요하기 때문에 다양한 자연영상을 대상으로 적용하면 성능 저하가 발생한다. 본 논문에서는 상기 언급한 문제점들을 극복할 수 있는 운동기반 관심맵 생성 방법을 제안한다. 공간 관심맵에 운동 정보를 결합하고, 운동 복잡도를 활용한다. 또한 근접 모델을 이용하여 주변 픽셀들의 관심도를 유사하게 함으로써, 동일 객체 또는 배경 영역이 유사한 값을 가지도록 한다. 실험에서는 다양한 동영상 데이터에 제안 방법을 적용하여 성능 검증을 수행하였다. 공간 관심도의 개선 여부를 증명하기 위해서 공간 관심맵 방법과의 객관적 성능 평가를 통해서 제안 방법이 공간 관심맵보다 운동 픽셀의 경우에 평균적으로 관심도 값이 +38 정도 향상되는 것을 보여준다. 또한 참조 데이터가 있는 4개의 동영상을 대상으로 얻은 ROC는 만족스러운 결과를 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4587-4605
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• 2019

High Efficiency Video Coding (HEVC) suffers from high computational complexity due to its quad-tree structure in motion estimation (ME). This paper exposes an adaptive search range decision algorithm for accelerating HEVC integer-pel ME on GPU which estimates the optimal search range (SR) using a MAP (Maximum A Posteriori) estimator. There are three main contributions; First, we define the motion feature as the standard deviation of motion vector difference values in a CTU. Second, a MAP estimator is proposed, which theoretically estimates the motion feature of the current CTU using the motion feature of a temporally adjacent CTU and its SR without any data dependency. Thus, the SR for the current CTU is parallelly determined. Finally, the values of the prior distribution and the likelihood for each discretized motion feature are computed in advance and stored at a look-up table to further save the computational complexity. Experimental results show in conventional HEVC test sequences that the proposed algorithm can achieves high average time reductions without any subjective quality loss as well as with little BD-bitrate increase.

• Investigative Magnetic Resonance Imaging
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• 제23권4호
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• pp.328-340
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• 2019

Purpose: To generate phase images with free of motion-induced artifact and susceptibility-induced distortion using 3D radial ultrashort TE (UTE) MRI. Materials and Methods: The field map was theoretically derived by solving Laplace's equation with appropriate boundary conditions, and used to simulate the image distortion in conventional spin-warp MRI. Manufacturer's 3D radial imaging sequence was modified to acquire maximum number of radial spokes in a given time, by removing the spoiler gradient and sampling during both rampup and rampdown gradient. Spoke direction randomly jumps so that a readout gradient acts as a spoiling gradient for the previous spoke. The custom raw data was reconstructed using a homemade image reconstruction software, which is programmed using Python language. The method was applied to a phantom and in-vivo human brain and abdomen. The performance of UTE was compared with 3D GRE for phase mapping. Local phase mapping was compared with T₂* mapping using UTE. Results: The phase map using UTE mimics true field-map, which was theoretically calculated, while that using 3D GRE revealed both motion-induced artifact and geometric distortion. Motion-free imaging is particularly crucial for application of phase mapping for abdomen MRI, which typically requires multiple breathold acquisitions. The air pockets, which are caught within the digestive pathway, induce spatially varying and large background field. T₂* map, that was calculated using UTE data, suffers from non-uniform T₂* value due to this background field, while does not appear in the local phase map of UTE data. Conclusion: Phase map generated using UTE mimicked the true field map even when non-zero susceptibility objects were present. Phase map generated by 3D GRE did not accurately mimic the true field map when non-zero susceptibility objects were present due to the significant field distortion as theoretically calculated. Nonetheless, UTE allows for phase maps to be free of susceptibility-induced distortion without the use of any post-processing protocols.

• 한국통신학회논문지
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• 제24권9A호
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• pp.1411-1418
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• 1999

본 논문에서는, 움직임 예측과 신경 회로망을 이용한 고속 움직임 추려하여, 현재 블록의 움직임 벡터를 인적 블록들의 움직임 벡터들로 예측하정 알고리즘을 제안하였다. 움직임 벡터의 공간적 상관성이 높다는 점을 고였다. 학습 시간이 빠르고 2차원 적응적 특성의 KSFM(Kohonen self-organizing feature map) 신경망을 이용하여, 움직임 벡터의 코드북(codebook)을 설계하였다. 2차원 코드북상에서 서로 비슷한 코드벡터들(codevectors)은 가까이 위치하므로, 예측 코드벡터로부터 코드북상에서 점진적으로 움직임을 추정하였다. 모의 실험 결과, 제안한 방법이 적은 계산량으로도 우수한 성능을 나타냄을 확인하였다.

• 대한임베디드공학회논문지
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• 제11권5호
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• pp.277-285
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• 2016

Moving object detection system has been an emerging research field in various advanced driver assistance systems (ADAS) and surveillance system. In this paper, we propose two optical flow based moving object detection methods at dynamic scenes. Both proposed methods consist of three successive steps; pre-processing, foreground segmentation, and post-processing steps. Two proposed methods have the same pre-processing and post-processing steps, but different foreground segmentation step. Pre-processing calculates mainly optical flow map of which each pixel has the amplitude of motion vector. Dense optical flows are estimated by using Farneback technique, and the amplitude of the motion normalized into the range from 0 to 255 is assigned to each pixel of optical flow map. In the foreground segmentation step, moving object and background are classified by using the optical flow map. Here, we proposed two algorithms. One is Gaussian mixture model (GMM) based background subtraction, which is applied on optical map. Another is adaptive thresholding based foreground segmentation, which classifies each pixel into object and background by updating threshold value column by column. Through the simulations, we show that both optical flow based methods can achieve good enough object detection performances in dynamic scenes.