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Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

作者： Lei Yuan Jinzong Li Bing Zhu Yulong Qiao Harbin Institute of Technology Harbin China

ISBN: (纸本)0780393953

Horn and Schunk's approach is a very classical optical flow algorithm. This paper investigates a modification of Horn and Schunk's approach which leads to a better preservation of flow discontinuities. It improves Horn-Schunk model in three aspects: (i) It replaces the smooth weight coefficient in the energy equation by variable weight coefficient, (ii) It adopts a new method to compute the velocity mean. The new method reflects the effect of the intensity difference on the image velocity diffusion, (iii) It introduces a more efficient iterative method than the Gauss-Seidel method to solve the associated Euler-Lagrange equation. The experiment results have validated the better effect of the improved method on discontinuities preserving.

关键词： image sequences motion estimation Euler-Lagrange equation Gauss-Seidel method Horn-Schunk model energy equation flow discontinuities preservation image velocity diffusion iterative method optical flow algorithm smooth weight coefficient variable weight c

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A Novel WasSAR Image Offset Information Estimation Method for 3-D Information Acquisition

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Li, Yishi Chen, Leping Song, Yongping Huang, Xiaotao An, Daoxiang Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China

The wide angle staring synthetic aperture radar (WasSAR), as an emerging synthetic aperture radar (SAR) observation mode, enables long-duration, multiangular imaging of a scene, demonstrating remarkable advantages in 3-D information acquisition. A critical step in the process of 3-D information extraction lies in accurately determining the displacement information between subaperture images captured from adjacent azimuth angles. During the WasSAR imaging process, spatial targets exhibit positional discrepancies in imaging results obtained from different azimuth perspectives, making pixel-wise displacement estimation in SAR images highly challenging, especially in complex scenarios. In order to address this challenge, this study proposes an innovative displacement estimation method for WasSAR imagery tailored for 3-D information extraction. The proposed approach begins with brightness equalization preprocessing to harmonize the brightness distribution between two images, ensuring the accuracy of subsequent processing steps. This is followed by an initial estimation using block-based registration techniques based on the enhanced correlation coefficient (ECC). Finally, an improved optical flow algorithm is employed to achieve precise displacement estimation, significantly enhancing the accuracy and reliability of displacement information estimation between SAR images. A series of experiments were conducted using Ku-band mountain scene datasets acquired by the National University of Defense Technology (NUDT). The experimental results include a comprehensive comparative analysis with several existing displacement estimation methods, showcasing the superior performance of the proposed algorithm across multiple key performance metrics. The proposed algorithm's performance in 3-D information extraction applications was also evaluated, confirming its effectiveness and high practicality.

关键词： 3-D information acquisition enhanced correlation coefficient (ECC) algorithm offset estimation optical flow algorithm synthetic aperture radar (SAR) image processing wide angle staring synthetic aperture radar (WasSAR) 3-D information acquisition enhanced correlation coefficient (ECC) algorithm offset estimation optical flow algorithm synthetic aperture radar (SAR) image processing wide angle staring synthetic aperture radar (WasSAR)

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A novel driving lane change intent prediction model based on image data mining approach and transformer

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ICT Express 2025年

作者： He, Junbo Guan, Wei Gou, Xuanyuan Zhang, Zhiqing Guangxi Science and Technology Development Institute Nanning 530001 China School of Aeronautical Engineering Civil Aviation University of China Tianjin 300300 China College of Mechanical Engineering Guangxi University Nanning 530004 China School of Mechanical and Automotive Engineering Guangxi University of Science and Technology Liuzhou 545000 China

Lane-changing represents not only a common driving behavior but also a potentially hazardous one. Accurately predicting lane change intentions plays a crucial role in enhancing road traffic safety and guiding autonomous vehicle planning. In this study, a Face-mesh model is used to extract salient features from complex driver behavior data. Subsequently, by using the Farneback optical flow algorithm in conjunction with the ResNet-50 neural network, important lane change cues were extracted from the vehicle surroundings. The Transformer model was optimized using the Teacher-forcing training strategy and the Scheduled-sampling method, fostering faster convergence and heightened prediction accuracy. Empirical tests had shown that this model had attained an impressive precision of 98.61%, recall of 98.24 %, and an F1 score of 98.42 % when forecasting lane change intentions 0.5 s ahead. © 2025 The Author(s)

关键词： Image data mining Lane change intention prediction Neural network optical flow algorithm

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Analog-VLSI, array-processor-based, Bayesian, multi-scale optical flow estimation

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2006年第1期34卷 49-75页

作者： Török, L Zarándy, A Hungarian Acad Sci Comp & Automat Res Inst Anal & Neural Comp Syst Lab H-1111 Budapest Hungary

optical flow (OF) estimation aims at derive a motion-vector field that characterizes motions on a video sequence of images. In this paper, we propose a new multi-scale (or scale-space) algorithm that generates OF on cellular neural/non-linear network universal machine, a general purpose analog-VLSI hardware, at resolution of 128 x 128 with fair accuracy and working over a speed of 100 frames/s. The performance of the hardware implementation of the proposed algorithm is measured on a standard image sequence. As far as we are concerned, this is the first time when an OF estimator hardware is tested on a practical-size standard image sequence. Copyright (c) 2006 John Wiley & Sons, Ltd.

关键词： multi-scale optical flow algorithm analog VLSI implementation cellular neural/non-linear network

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Estimation of water flow velocity in small plants using cold neutron imaging with D₂O tracer

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NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2009年第1-2期605卷 146-149页

作者： Matsushima, U. Herppich, W. B. Kardjilov, N. Graf, W. Hilger, A. Manke, I. Iwate Univ Fac Agr Morioka Iwate Japan Leibniz Inst Agr Engn Dept Hort Engn Potsdam Germany Helmholtz Ctr Berlin Mat & Energy SF3 Berlin Germany Humboldt Univ Inst Hort Sci D-1086 Berlin Germany

Water flow imaging may help to better understand various problems related to water stress of plants. It may help to fully understand the water relations of plants. The objective of this research was to estimate the velocity of water flow in plant samples. Cut roses (Rosa hybrida, var. 'Milva') were used as samples. Cold neutron radiography (CNR) was conducted at CONRAD, Helmholtz Center Berlin for Materials and Energy, Berlin, Germany. D2O and H2O were interchangeably injected into the water feeding system of the sample. After the uptake of D2O, the neutron transmission increased due to the smaller attenuation coefficient of D2O compared to H2O. Replacement of D2O in the rose peduncle was clearly observed. Three different optical flow algorithms, Block Matching, Horn-Schunck and Lucas-Kanade, were used to calculate the vector of D2O tracer flow. The quality of sequential images providing sufficient spatial and temporal resolution allowed to estimate flow vector. (C) 2009 Published by Elsevier B.V.

关键词： Vector optical flow algorithm Rose Block Matching

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optical flow Based Violence Detection in Video Surveillance 1

Optical Flow Based Violence Detection in Video Surveillance

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1st International Conference on Advances in Communication and Computing Technology (ICACCT)

作者： Garje, Prasad. D. Nagmode, M. S. Davakhar, Kiran. C. Zeal Coll Engn & Res Pune Maharashtra India Govt Coll Engn & Res E&TC Dept Pune Maharashtra India Smt Kashibai Navale Coll Engn E&TC Dept Pune Maharashtra India

ISBN: (纸本)9781538609262

Video Surveillance has become an issue of utmost importance due to rising crime and violence rate in the world. Many algorithms exist to analyze the behavior of the moving objects. In this paper, an approach to detect any violent behavior in videos using optical flow algorithms. The SDHA 2000 dataset is used to analyze foreground behavior. The main task in violence detection is to detect moving objects and classify their behavior using mean of intensity as violent or non-violent.

关键词： RGB to HSV Conversion optical flow algorithm Gunner Farneback algorithm Violent Activity

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Side Information Generation Using optical flow and Block Matching in Wyner-Ziv Video Coding 21

Side Information Generation Using Optical Flow and Block Mat...

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2014 21st IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Taheri, Y. Mohammad Ahmad, M. Omair Swamy, M. N. S. Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada

ISBN: (纸本)9781479942428

In this work, a new algorithm to generate high quality side information in Wyner-Ziv video coding is proposed. A block-matching algorithm is incorporated into the forward and backward optical flow and warping algorithms to find the forward and backward motion fields that are used for frame interpolation. Also, a symmetric optical flow algorithm for the purpose of frame interpolation is obtained by parameter modification in the energy functional of an optical flow algorithm. The average of the interpolated frames estimated using the forward/ backward motion fields and symmetric flow is used to provide a high quality side information frame for decoding of the corresponding Wyner-Ziv frame in the Wyner-Ziv video coding problem. The proposed algorithm significantly improves the quality of the side information frames compared with those provided by the advanced block matching frame interpolation in the typical Wyner-Ziv video codecs. Simulation results showing significant improvements in side information quality and rate-distortion performance in Wyner-Ziv video coding are provided.

关键词： image matching interpolation motion estimation video coding Wyner-Ziv frame Wyner-Ziv video coding advanced block matching frame interpolation backward motion fields backward optical flow block matching algorithm energy functional forward motion fields forward optical flow forward-backward motion fields frame interpolation interpolated frames optical flow optical flow algorithm parameter modification side information frames side information generation Codecs Decoding Interpolation optical imaging PSNR Vectors Video coding Video coding Optic flow frame interpolation Parameter modification Interpolation block matching codecs DECODING image matching Peak signal-to-noise ratio optical Imaging motion estimation

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Study on Non-rigid Medical Image Registration Based on optical flow Model

Study on Non-rigid Medical Image Registration Based on Optic...

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International Workshop on Image Processing and optical Engineering (IPOE)/International Conference on Information, Computing, and Telecommunications (ICICT)

作者： Lu Xiaoqi Zhao Yongjie Zhang Baohua Ma Hongli Inner Mongolia Univ Sci & Technol Sch Informat Engn Baotou 014010 Peoples R China

ISBN: (纸本)9780819489920

A new method for image registration based on step-by-step registration is proposed. First, SIFT feature algorithm is used to image to get rough registration then optical flow algorithm is used to achieve the final accurate registration. Image feature point extraction is the basis of medical image registration and its accuracy impacts on the matching results directly. SIFT feature algorithm is based on local image features and has a good feature of scale, rotation, illumination invariant. optical flow algorithm no need to do feature extraction and this method calculation is quick and simple and it uses image intensity information directly. The two steps are complementary that the former prepare for the latter to improve the convergence rate while the latter allows a more accurate registration result. The experimental results show that this algorithm can improve the efficiency of non-rigid medical image registration accuracy and increase convergence speed thus it has certain superiority in terms of image registration.

关键词： non-rigid registration medical image step-by-step registration SIFT feature algorithm optical flow algorithm

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Point constrained optical flow for LV motion detection

Point constrained optical flow for LV motion detection

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Medical Imaging 2000 Conference

作者： Loncaric, S Macan, T Univ Zagreb Fac Elect Engn & Comp Zagreb 41000 Croatia

ISBN: (纸本)0819435953

In this paper, we propose a new method for left ventricle (LV) motion estimation. The method is based on a point-constrained optical flow algorithm for heart motion estimation. The constrained points are the corresponding point pairs in subsequent images. The motion estimation of these characteristic points can be obtained using techniques such as shape-based tracking of perceptually salient points on the LV boundary. Knowing the motion of characteristic points the proposed algorithm is used to estimate motion at other image points. Using this approach the result of the optical flow algorithm is constrained by displacement of characteristic LV boundary points. The constraints are implemented by setting the values of the optical flow of characteristic points to certain fixed values. The spatial and temporal continuity functionals are specified so that the fixed values influence their neighborhoods and the optical now field is interpolated between the constrained points. The experiments have been performed using ECG-gated MR images of the beating heart. The method has been applied to the image sequence and estimation of the motion field has been computed.

关键词： motion detection optical flow algorithm cardiac image analysis medical imaging motion estimation

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Deepfake Video Detection Based on Improved CapsNet and Temporal–Spatial Features

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Computers, Materials & Continua 2023年第4期75卷 715-740页

作者： Tianliang Lu Yuxuan Bao Lanting Li People’s Public Security University of China Beijing100038China

Rapid development of deepfake technology led to the spread of forged audios and videos across network platforms,presenting risks for numerous countries,societies,and individuals,and posing a serious threat to cyberspace *** address the problem of insufficient extraction of spatial features and the fact that temporal features are not considered in the deepfake video detection,we propose a detection method based on improved CapsNet and temporal–spatial features(iCapsNet–TSF).First,the dynamic routing algorithm of CapsNet is improved using weight initialization and ***,the optical flow algorithm is used to extract interframe temporal features of the videos to form a dataset of temporal–spatial ***,the iCapsNet model is employed to fully learn the temporal–spatial features of facial videos,and the results are *** results show that the detection accuracy of iCapsNet–TSF reaches 94.07%,98.83%,and 98.50%on the Celeb-DF,FaceSwap,and Deepfakes datasets,respectively,displaying a better performance than most existing mainstream *** iCapsNet–TSF method combines the capsule network and the optical flow algorithm,providing a novel strategy for the deepfake detection,which is of great significance to the prevention of deepfake attacks and the preservation of cyberspace security.

关键词： Deepfake detection CapsNet optical flow algorithm temporal–spatial features

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