• 제목/요약/키워드: Map of Gradient

검색결과 191건 처리시간 0.032초

Hierarchical Fuzzy Motion Planning for Humanoid Robots Using Locomotion Primitives and a Global Navigation Path

  • Kim, Yong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권3호
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    • pp.203-209
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    • 2010
  • This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

흐린 초점의 단일영상에서 깊이맵 생성 알고리즘 (Depth Map Generation Algorithm from Single Defocused Image)

  • 이용환;김영섭
    • 반도체디스플레이기술학회지
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    • 제15권3호
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    • pp.67-71
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    • 2016
  • This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.

HÖLDER CONVERGENCE OF THE WEAK SOLUTION TO AN EVOLUTION EQUATION OF p-GINZBURG-LANDAU TYPE

  • Lei, Yutian
    • 대한수학회지
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    • 제44권3호
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    • pp.585-603
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    • 2007
  • The author studies the local $H\ddot{o}lder$ convergence of the solution to an evolution equation of p-Ginzburg-Landau type, to the heat flow of the p-harmonic map, when the parameter tends to zero. The convergence is derived by establishing a uniform gradient estimation for the solution of the regularized equation.

3차원 작업공간에서 보행 프리미티브를 이용한 다리형 로봇의 운동 계획 (Motion Planning for Legged Robots Using Locomotion Primitives in the 3D Workspace)

  • 김용태;김한정
    • 로봇학회논문지
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    • 제2권3호
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    • pp.275-281
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    • 2007
  • This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

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불균일 자장 보정 후처리 기법을 이용한 간 영상에서의 지방 및 $T_2{^*}$ 측정 (Background Gradient Correction using Excitation Pulse Profile for Fat and $T_2{^*}$ Quantification in 2D Multi-Slice Liver Imaging)

  • 남윤호;김한성;조상영;김동현
    • Investigative Magnetic Resonance Imaging
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    • 제16권1호
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    • pp.6-15
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    • 2012
  • 목적: 이 연구의 목적은 excitation pulse profile을 이용하여 불균일 자장에 의하여 발생하는 배경 경사 자장에 의한 영향을 보상하여 2차원 다중 단면 경사에코 간 영상에서의 정확한 지방 및 $T_2{^*}$ 측정을 하는 데에 있다. 대상과 방법: 2차원 경사에코영상에서 불균일 자장에 의한 배경경사자장으로 인하여 유도되는 신호의 감소는 excitation pulse profile weighting으로 나타난다. 이에 의한 영향을 최소화 하기 위하여 $B_0$ field map을 통하여 단면선택방향으로의 선형 경사자장의 정도를 추정한 후, 획득한 신호를 excitation pulse profile을 이용하여 보정하였다. $T_2{^*}$ 및 지방은 보정된 신호로부터 측정되었으며 보정방법은 3.0T 임상용 장비에서 팬텀 및 in vivo 실험을 통하여 이루어 졌다. 결과: 팬텀 실험 결과는 보정 후 측정된 $T_2{^*}$ 및 지방의 양이 자장이 균일한 경우에 가까워 진 것을 보여 주었다. In vivo 실험에서는 간에서 배경경사자장의 크기가 약 120 ${\mu}T/m$ 정도 까지로 나타났으며 보정하기 전에 비하여 측정된 $T_2{^*}$ 및 지방의 정도의 균일도가 높아지는 것을 확인할 수 있었다. 결론: Excitation pulse profile을 이용한 배경경사자장 보정 방법은 경사 에코 신호에서의 거시적인 불균일 자장에 의한 영향을 줄여 주며 2차원 간 영상에서의 적용을 통하여 보다 정확한 지방 및 $T_2{^*}$의 측정에 도움이 될 수 있다.

Performance Comparison of Machine-learning Models for Analyzing Weather and Traffic Accident Correlations

  • Li Zi Xuan;Hyunho Yang
    • Journal of information and communication convergence engineering
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    • 제21권3호
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    • pp.225-232
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    • 2023
  • Owing to advancements in intelligent transportation systems (ITS) and artificial-intelligence technologies, various machine-learning models can be employed to simulate and predict the number of traffic accidents under different weather conditions. Furthermore, we can analyze the relationship between weather and traffic accidents, allowing us to assess whether the current weather conditions are suitable for travel, which can significantly reduce the risk of traffic accidents. In this study, we analyzed 30000 traffic flow data points collected by traffic cameras at nearby intersections in Washington, D.C., USA from October 2012 to May 2017, using Pearson's heat map. We then predicted, analyzed, and compared the performance of the correlation between continuous features by applying several machine-learning algorithms commonly used in ITS, including random forest, decision tree, gradient-boosting regression, and support vector regression. The experimental results indicated that the gradient-boosting regression machine-learning model had the best performance.

Real-Time 2D-to-3D Conversion for 3DTV using Time-Coherent Depth-Map Generation Method

  • Nam, Seung-Woo;Kim, Hye-Sun;Ban, Yun-Ji;Chien, Sung-Il
    • International Journal of Contents
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    • 제10권3호
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    • pp.9-16
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    • 2014
  • Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

Gradient Vector Flow을 이용한 의료영상 분할 (Medical Image Segmental ion using Gradient Vector Plow)

  • 김진철;김종욱;이배호;정태웅
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (2)
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    • pp.478-480
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    • 2002
  • 영상 분할은 임상에서의 진단과 분석 및 3차원 가시화를 위해 선행되어야 할 필수 과정이다. 의료영상은 영상이 가지는 데이터 자체의 고유한 제약들과 해부학적 변이성 때문에 영상분할에 어려움이 있다. 본 논문에서는 의료영상의 분할을 위해 스네이크의 새로운 외부 힘으로 Gradient Vector Flow(GVF)를 이용한 방법을 제안한다. 제안된 방법은 2차원 의료영상에서 에지 맵(edge map)을 구하고, GVF을 계산하여 스네이크의 경계선과 같이 관심 있는 특징의 에너지 함수가 최소가 되는 GVF 스네이크(snake)를 구한다. 제안된 방법을 초음파영상과 자기공명영상 같은 의료영상의 분할에 적용한 결과 기존의 스네이크와 달리 잡음이나 오목한 부분이 있는 객체들을 성공적으로 분할하였다.

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No-reference Sharpness Index for Scanning Electron Microscopy Images Based on Dark Channel Prior

  • Li, Qiaoyue;Li, Leida;Lu, Zhaolin;Zhou, Yu;Zhu, Hancheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권5호
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    • pp.2529-2543
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    • 2019
  • Scanning electron microscopy (SEM) image can link with the microscopic world through reflecting interaction between electrons and materials. The SEM images are easily subject to blurring distortions during the imaging process. Inspired by the fact that dark channel prior captures the changes to blurred SEM images caused by the blur process, we propose a method to evaluate the SEM images sharpness based on the dark channel prior. A SEM image database is first established with mean opinion score collected as ground truth. For the quality assessment of the SEM image, the dark channel map is generated. Since blurring is typically characterized by the spread of edge, edge of dark channel map is extracted. Then noise is removed by an edge-preserving filter. Finally, the maximum gradient and the average gradient of image are combined to generate the final sharpness score. The experimental results on the SEM blurred image database show that the proposed algorithm outperforms both the existing state-of-the-art image sharpness metrics and the general-purpose no-reference quality metrics.