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arXiv 2019年

作者： Yuan, Ye Li, Junlin Li, Liang Jiang, Frank Tang, Xiuchuan Zhang, Fumin Liu, Sheng Goncalves, Jorge Voss, Henning U. Li, Xiuting Kurths, Jürgen Ding, Han School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30332 United States School of Power and Mechanical Engineering Wuhan University Wuhan430074 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Luxembourg Centre for Systems Biomedicine University of Luxembourg BelvauxL-4367 Luxembourg Citigroup Biomedical Imaging Center Weill Cornell Medical College New York10021 United States Research Domain IV - Transdisciplinary Concepts & Methods Potsdam Institute for Climate Impact Research Potsdam14473 Germany School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal System Discovery (S3d), decides which physical terms are necessary and which can be removed (because they are physically negligible in the sense that they do not affect the dynamics too much) from a pool of candidate functions. The method is built on the recent development of Sparse Bayesian Learning;which enforces the sparsity in the to-be-identified PDEs, and therefore can balance the model complexity and fitting error with theoretical guarantees. Without leveraging prior knowledge or assumptions in the discovery process, we use an automated approach to discover ten types of PDEs, including the famous Navier-Stokes and sine-Gordon equations, from simulation data alone. Moreover, we demonstrate our data-driven discovery process with the Complex Ginzburg-Landau Equation (CGLE) using data measured from a traveling-wave convection experiment. Our machine discovery approach presents solutions that has the potential to inspire, support and assist physicists for the establishment of physical laws from measured spatiotemporal data, especially in notorious fields that are often too complex to allow a straightforward establishment of physical law, such as biophysics, fluid dynamics, neuroscience or nonlinear optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear optics

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Optimization Techniques in Computer Vision 1

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丛书名： Advances in Computer Vision and Pattern Recognition

2016年

作者： Mongi A. Abidi Andrei V. Gribok Joonki Paik

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Robust feature detection using particle keypoints and its application to video stabilization in a consumer handheld camera

Robust feature detection using particle keypoints and its ap...

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IEEE International Conference on Consumer Electronics, ICCE 2016

作者： Jeon, Semi Yoon, Inhye Yang, Seung'I Kim, Bongmo Kim, Jisung Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Video Technology Lab. Future Technology RandD Division SK Telecom Korea Republic of

ISBN: (纸本)9781467383646

Compact, portable digital cameras have been popular to consumers. This paper presents a robust feature detection method using particle keypoints and its application to video stabilization. The proposed video stabilization algorithm consists of three steps: i) generation of a flat region map based on the Gaussian filter, ii) robust feature point detection using particle keypoints, and iii) camera paths estimation for enhancing a shaky video. As a result, the proposed algorithm can estimate optimal homography by redefining important feature points using particle keypoints in the flat region map. The proposed robust feature detection algorithm is suitable for enhancing the quality of video acquired by consumer handheld imaging devices. © 2016 IEEE.

关键词： Stabilization

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Hand detection using facial information

Hand detection using facial information

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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Sangpil Han Seokmok Park Min-jae Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science and Film Chung-Ang University Seoul Korea

This paper presents a robust hand detection algorithm using the facial information. The proposed algorithm consists of four steps: (i) detection of a face, (ii) generation of regions of interest (ROI) to detect hands, (iii) skin color extraction from the face region, and (iv) detection of hands using the face skin color in the ROI. The proposed algorithm can reduce false detection caused by a similar skin color, and provides a successful detection rate up to 92 percent.

关键词： Face Skin Color Detection algorithms image color analysis Robustness Face detection

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Robust feature detection using particle keypoints and its application to video stabilization in a consumer handheld camera

Robust feature detection using particle keypoints and its ap...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Semi Jeon Inhye Yoon Seung'i Yang Bongmo Kim Jisung Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Multimedia and Film Chung-Ang University Seoul Korea Future Technology R&D Division Video Technology Lab.

关键词： Conferences Consumer electronics

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New corner detector using non-cornerness measure

New corner detector using non-cornerness measure

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IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia)

作者： Woon Cho Seokmok Park Jacob D'avy Joonki Paik The University of Tennessee Knoxville TN USA Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science and Film Chung-Ang University Seoul Korea University of Tennessee Knoxville Knoxville TN US

In this paper, we present a novel corner detection method based on a new non-cornerness measure. The non-cornerness function is comprised of two steps: 1) eliminate any pixel located in a flat region and 2) remove a pixel that is positioned along an edge in any orientation. The experimental results show that our proposed method outperforms previous corner detectors.

关键词： Detectors image edge detection Indexes Boundary conditions Computer vision Real-time systems Information and communication technology

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Imaging inverse problem using sparse representation with adaptive dictionary learning 5

Imaging inverse problem using sparse representation with ada...

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2015 5th IEEE International Advance Computing Conference, IACC 2015

作者： Mittu George, P. Vivek, M. Paik, Joonki Oxford College of Engineering Bangalore India Image Processing and Intelligent Systems Laboratory Chung-Ang University Seoul Korea Republic of

ISBN: (纸本)9781479980475

Sparse representation is one of the powerful emerging statistical techniques for modeling images. This representation approximates the image as a combination of the codewords within a dictionary which is over complete. Recent years have seen a tremendous growth in the field of sparse representation. Here a method is proposed for image inversing by using iterative deblurring based on sparse representation of an image which is uniformly blurred. The key idea behind this methodology is the sparseness of natural images in some domain. The quality of recovered image majorly depends on the domain or the dictionaries that are used to represent it. In this paper, the K-SVD algorithm is used to train thegroup of codewords from a set of quality natural image patches. For each of the local patch within the blurred image, the best suited sub-dictionary from the trained dictionary data base is selected. In addition, a smoothness regularization constraint is added that prevents the reblurring of the image edges. For numerical stability the sparsity weight is adaptively computed which also improves the reconstructed image quality. Comparative study on some of the existing restoration algorithm proves the proposed method outperforms them all. © 2015 IEEE.

关键词： image reconstruction

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A multi-agent coordinated planning approach for deadline required emergency response tasks

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IET Control Theory and Applications 2015年第3期9卷 447-455页

作者： Zhou, Chao Wang, Hongwei Zhuo, Hankz Hankui Key Laboratory of Image Processing and Intelligent Control of Education Ministry Institute of Systems Engineering Huazhong University of Science and Technology Wuhan430074 China School of Advanced Computing SunYat-sen University Guangzhou510006 China

This study investigates the emergency decision-making problem in a multi-agent system. Departments are modeled as agents to perform coordinated planning to obtain a global action plan with a short execution time constrained by a prescribed deadline. A novel multi-agent planning approach is proposed to coordinate for the solution among agents in the system. The approach consists of two stages. For the first stage, a coordinated planning and scheduling method is designed to generate a candidate global action plan. In this plan, durative actions are assigned to proper time intervals with the consideration of temporal relationships among agents. For the second stage, a coordination mechanism based on local heuristics is proposed to reduce the global time cost of the candidate plan to satisfy the deadline. An experimental study of emergency evacuation problem is conducted to demonstrate the effectiveness and efficiency of the proposed approach. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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Leg hybrid rehabilitation based on hip-knee exoskeleton and ankle motion induced by FES

Leg hybrid rehabilitation based on hip-knee exoskeleton and ...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xikai Tu Jian Huang Jiping He Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA School of Mechatronic Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509033652

To regain mobility, stroke patients need to receive repetitive and intensive therapy. Robot-assisted rehabilitation is an active area of research. Cheap robotic leg rehabilitation devices should be developed to meet the demands and assist most patients. A low cost hip-knee exoskeleton prototype powered by pneumatic muscles was developed. On this basis, Functional Electrical Stimulation (FES) induced paralyzed muscles to realize ankle joint rehabilitation training. As both of pneumatic muscle and FES induced muscle possess highly nonlinear characteristics, a sliding control algorithm called Chattering mitigation Robust Variable Control (CRVC) was applied to leg hybrid rehabilitation. The combination of exoskeleton and FES is a promising way to reduce the cost and the complexity of designing hip-knee-ankle exoskeleton. The proposed hybrid method is verified by treadmill-based gait training experiments.

关键词： Muscles Exoskeletons Mathematical model Legged locomotion Iron Training

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Video stabilization using classification-based homography estimation for consumer video camera

Video stabilization using classification-based homography es...

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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Inhye Yoon Semi Jeon Seokhwa Jeong Joonki Paik Image Processing and Intelligent Systems Laboratory Chung-Ang University Seoul Korea

Handheld camera such as a mobile phone, action camera, and portable camcorder suffer from video instability due to unintentional shakes. This paper presents a video stabilization approach to enhance a shaky video acquired by consumer handheld camera. The proposed algorithm consists of three steps: i) generation of the binary image based on vertical class, ii) estimation of homography, and iii) frame warping for enhancing a shaky video. As a result, the proposed algorithm can remove undesired motions using optimal camera motion trajectory based on feature detection in the background region. The proposed video stabilization algorithm is suitable for consumer video devices including advanced driver assistance systems (ADAS), video surveillance systems, and aerial platforms for video enhancement.

关键词： Cameras Trajectory Streaming media Feature extraction Estimation Prediction algorithms Kalman filters

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