Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

Three-dimensional color particle image velocimetry based on a cross-correlation and optical flow method

Rainbow particle image velocimetry(PIV)can restore the three-dimensional velocity field of particles with a single camera;however,it requires a relatively long time to complete the reconstruction.This paper proposes a hybrid algorithm that combines the fast Fourier transform(FFT)based co-correlation algorithm and the Horn–Schunck(HS)optical flow pyramid iterative algorithm to increase the reconstruction speed.The Rankine vortex simulation experiment was performed,in which the particle velocity field was reconstructed using the proposed algorithm and the rainbow PIV method.The average endpoint error and average angular error of the proposed algorithm were roughly the same as those of the rainbow PIV algorithm;nevertheless,the reconstruction time was 20%shorter.Furthermore,the effect of velocity magnitude and particle density on the reconstruction results was analyzed.In the end,the performance of the proposed algorithm was verified using real experimental single-vortex and double-vortex datasets,from which a similar particle velocity field was obtained compared with the rainbow PIV algorithm.The results show that the reconstruction speed of the proposed hybrid algorithm is approximately 25%faster than that of the rainbow PIV algorithm.

FeatureMatching Combining Variable Velocity Model with Reverse Optical Flow

The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion,which leads to a false matching,with an inaccurate pose estimation or failed tracking.To address the challenge above,a new method of feature point matching is proposed in this paper,which combines the variable velocity model with the reverse optical flow method.First,the constant velocity model is extended to a new variable velocity model,and the expanded variable velocity model is used to provide the initial pixel shifting for the reverse optical flow method.Then the search range of feature points is accurately determined according to the results of the reverse optical flow method,thereby improving the accuracy and reliability of feature matching,with strengthened interframe tracking effects.Finally,we tested on TUM data set based on the RGB-D camera.Experimental results show that this method can reduce the probability of tracking failure and improve localization accuracy on SLAM(Simultaneous Localization and Mapping)systems.Compared with the traditional ORB-SLAM2,the test error of this method on each sequence in the TUM data set is significantly reduced,and the root mean square error is only 63.8%of the original system under the optimal condition.

6-DOF motion estimation using optical flow based on dual cameras

Because of its characteristics of simple algorithm and hardware, optical flow-based motion estimation has become a hot research field, especially in GPS-denied environment. Optical flow could be used to obtain the aircraft motion information, but the six-(degree of freedom)(6-DOF) motion still couldn't be accurately estimated by existing methods. The purpose of this work is to provide a motion estimation method based on optical flow from forward and down looking cameras, which doesn't rely on the assumption of level flight. First, the distribution and decoupling method of optical flow from forward camera are utilized to get attitude. Then, the resulted angular velocities are utilized to obtain the translational optical flow of the down camera, which can eliminate the influence of rotational motion on velocity estimation. Besides, the translational motion estimation equation is simplified by establishing the relation between the depths of feature points and the aircraft altitude. Finally, simulation results show that the method presented is accurate and robust.

Discontinuity-preserving optical flow algorithm

A modification of Horn and Schunk＇s approach is investigated, which leads to a better preservation of flow discontinuities. It improves Horn-Schunk model in three aspects： （1） It replaces the smooth weight coefficient in the energy equation by the variable weight coefficient. （2） It adopts a novel method to compute the mean velocity. The novel method also reflects the effect of the intensity difference on the image velocity diffusion. （3） It introduces a more efficient iterative method than the Gauss-Seidel method to solve the associated Euler-Lagrange equation. The experiment results validate the better effect of the improved method on preserving discontinuities.

An Underwater Image Bubble Noise Removal Method Based on Optical Flow

It is very important for underwater robots to accurately detect and locate target objects. However,under many circumstances,it is difficult to clearly observe the target object due to the existence of bubble noise. In this paper,we proposed a method to solve this problem. First,we used the LK optical flow algorithm to calculate the motion vector of the image background and compensate for the background motion.Then,the optical flow field of the bubbles was calculated by the HS optical flow algorithm,and the area where the bubble existed was obtained by binarizing the image. Finally,we used the adjacent frame image to repair the bubble area. We carried out a bubble noise removal experiment. The results show that this method can effectively remove the bubble noise in the image.

Analysis of spectrum characteristics of optical scintillation in stack gas flow

Based on the analysis of spectrum characteristics of intensity fluctuations while light beams pass through stack gas flow in an industrial setting, this paper puts emphasis upon discussing the spectrum of optical intensity fluctuations by the variety of particle concentration in stack gas flow. This paper also gives the primary theoretical explanation of the measurement results in the stack of coal-fired utility boilers. Meanwhile, the cross-correlation formula is given as the theoretical basis of velocity measurement by using particle concentration scintillation.

Evaluation of childhood developing via optical coherence tomography-angiography in Qamdo,Tibet,China:A prospective cross-sectional,school-based study

BACKGROUND Optical coherence tomography angiography(OCTA)is a new and reliable machine used to evaluate retinal structure and macular perfusion in children.The use of OCTA under bad condition such as high altitude,low atmospheric oxygen,and low humidity,in children is rarely.AIM To quantify the macular micro-vasculature in healthy children of various ages using OCTA in Qamdo.METHODS Design:Prospective cross-sectional,school-based study.Three hundred and fortyseven normal students from 9 schools in 4 different areas in Qamdo were included.OCTA was performed on a 3 mm×3 mm area centered on the macular region and macular cube 512×128 showed details in macular.Early treatment of diabetic retinopathy study Vessel Flow Density(VD)of the macular central vascular plexus density(CVD),inner vascular plexus density(IVD),full vascular plexus density(FVD),and the size of the foveal avascular zone(FAZ)were measured.All these results corrected by t/s=3.382×0.01306×(axial length-1.82).The differences were compared among various ages,sexes and living environments.RESULTS The mean FAZ area in all eyes was 0.27 mm^(2)±0.12 mm^(2).The mean foveal thickness(MFT)in the macular cube was 227.64μm±23.51μm.Compared with girls,boys had a lager FAZ(P=0.0029).Among the different age groups,MFT(P<0.001)and FVD(P<0.0001),IVD(P<0.0001),and CVD(P=0.0050)increased with age.FAZ areas were not correlated with age(P=0.8853)or others(MFT,area).CONCLUSION OCTA can use to evaluate macular perfusion in children.Our data bridge the gap between structural OCT and perfusion density in children in high altitude.Even though these were not a longitudinal study,it may provide us with hints about retina development during puberty and clinical implications of OCTA in children.

APPLICATION OF DOPPLER OPTICAL COHERENCE TOMOGRAPHY IN RHEOLOGICAL STUDIES:BLOOD FLOW AND VESSELS MECHANICAL PROPERTIES EVALUATION

Doppler Optical Coherence Tomography(DOCT)is a noninvasive optical diagnostic technique,which is well suited for the quantitative mapping of microflow velocity profiles and the analysis of flow-vessel interactions.The noninvasive imaging and quantitative analysis of blood flow in the complex-structured vascular bed is required in many biomedical applications,including those where the determination of mechanical properties of vessels or the knowledge of the mechanic interactions between the flow and the housing medium plays a key role.The change of microvessel wall elasticity could be a potential indicator of cardiovascular disease at the very early stage,whilst monitoring the blood flow dynamics and associated temporal and spatial variations in vessel’s wall shear stress could help predicting the possible rupture of atherosclerotic plaques.The results of feasibility studies of application of DOCT for the evaluation of mechanical properties of elastic vessel model are presented.The technique has also been applied for imaging of sub-cranial rat blood flow in vivo.

Abnormal Crowd Behavior Detection Based on the Entropy of Optical Flow

To improve the detection accuracy and robustness of crowd anomaly detection,especially crowd emergency evacuation detection,the abnormal crowd behavior detection method is proposed.This method is based on the improved statistical global optical flow entropy which can better describe the degree of chaos of crowd.First,the optical flow field is extracted from the video sequences and a 2D optical flow histogram is gained.Then,the improved optical flow entropy,combining information theory with statistical physics is calculated from 2D optical flow histograms.Finally,the anomaly can be detected according to the abnormality judgment formula.The experimental results show that the detection accuracy achieved over 95%in three public video datasets,which indicates that the proposed algorithm outperforms other state-of-the-art algorithms.

Study on Local Optical Flow Method Based on YOLOv3 in Human Behavior Recognition

In the process of human behavior recognition, the traditional dense optical flow method has too many pixels and too much overhead, which limits the running speed. This paper proposed a method combing YOLOv3 (You Only Look Once v3) and local optical flow method. Based on the dense optical flow method, the optical flow modulus of the area where the human target is detected is calculated to reduce the amount of computation and save the cost in terms of time. And then, a threshold value is set to complete the human behavior identification. Through design algorithm, experimental verification and other steps, the walking, running and falling state of human body in real life indoor sports video was identified. Experimental results show that this algorithm is more advantageous for jogging behavior recognition.

A Comprehensive UAV Indoor Navigation System Based on Vision Optical Flow and Laser FastSLAM

这份报纸论述为室内的 quadrotor 的全面控制，航行，本地化和印射的答案无人的天线车辆(UAV ) 系统。三个主要传感器在 quadrotor 站台上被使用，也就是，一个惯性的测量单位，一个向下看起来的照相机和扫描激光变化查找者。与这安装， UAV 能要用体力地估计它的自己的速度和位置，当没有碰撞，沿着一个房间的内部墙飞时。在一个以后完成飞行，与收集了数据历史性的 UAV 路径和室内的环境能很好被估计。系统的自治航行部分不要求任何遥远的感觉信息或离线的计算力量，当印射被做时离线。完全的飞行测试被执行了验证忠实和性能航行答案。

An Improved Optical Flow Method for Image Registration with Large-scale Movements

在这份报纸，为图象登记的一个改进光流动方法被建议。它以它与一个起始的运动评估者改进光流动方法的方法是新奇的：扩大了阶段关联技术(EPCT ) ，用补偿前者的缺乏的后者的优点。以一种更多的详细方式，光流动方法能到达亚象素精确性并且计算象啁啾并且倾斜一样的复杂失真模式，这能被说但是与大规模运动弱。因为 EPCT 用象素水平精确性盖住大翻译和旋转的大小并且在精明的负担是有效的，它能为光流动方法被当作一个好起始的运动评估者。测试证明了特别，这个改进方法将显著地与大规模运动为图象提高登记表演并且对随机的噪音柔韧。

A Closed Form Solution to Segment 3D Motion Using Straight-line Optical Flow

A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.

A novel algorithm for ocean wave direction inversion from X-band radar images based on optical flow method

As one of the important sea state parameters for navigation safety and coastal resource management, the ocean wave direction represents the propagation direction of the wave. A novel algorithm based on an optical flow method is developed for the ocean wave direction inversion of the ocean wave fields imaged by the X-band radar continuously. The proposed algorithm utilizes the echo images received by the X-band wave monitoring radar to estimate the optical flow motion, and then the actual wave propagation direction can be obtained by taking a weighted average of the motion vector for each pixel. Compared with the traditional ocean wave direction inversion method based on frequency-domain, the novel algorithm is fully using a time-domain signal processing method without determination of a current velocity and a modulation transfer function（MTF）. In the meantime,the novel algorithm is simple, efficient and there is no need to do something more complicated here. Compared with traditional ocean wave direction inversion method, the ocean wave direction of derived by using this proposed method matches well with that measured by an in situ buoy nearby and the simulation data. These promising results demonstrate the efficiency and accuracy of the algorithm proposed in the paper.

Research on HS Optical Flow Algorithm Based on Motion Estimation Optimization

The amount of computation for detecting moving objects by the optical flow algorithm is large. The optical flow information in the smooth region cannot be detected by the optical flow algorithm, and it is susceptible to noise in a complicated environment. In this study, an optimized Horn-Schunck (HS) optical flow algorithm based on motion estimation is proposed. To detect Harris corner in the image, the proposed algorithm is used in combination with the motion estimation algorithm based on macroblock to determine the region of interest (ROI) [1]. The ROI is then used as the initial motion vector for HS calculation to obtain the optical flow information. Filtering is conducted to eliminate the background noise. Experimental result shows that the application of the proposed algorithm improves the computational speed, avoids the interference of background noise, and enhances the robustness of HS. Moreover, the algorithm solves the problem rooted in the inability of the HS algorithm to detect the smooth part of optical flow information [2].

A ROBUST OPTICAL FLOW COMPUTATION

This paper presents a new method for robust and accurate optical flow estimation.The sig- nificance of this work is twofold.Firstly,the idea of bi-directional scheme is adopted to reduce the model error of optical flow equation,which allows the second order Taylor's expansion of optical flow equation for accurate solution without much extra computational burden;Secondly,this paper establishs a new optical flow equation based on LSCM (Local Structure Constancy Model) instead of BCM (Brightness Constancy Model),namely the optical flow equation does not act on scalar but on tensor-valued (ma- trix-valued) field,due to the two reason:(1) structure tensor-value contains local spatial structure information,which provides us more useable cues for computation than scalar;(2) local image structure is less sensitive to illumination variation than intensity,which weakens the disturbance of non-uniform illumination in real sequences.Qualitative and quantitative results for synthetic and real-world scenes show that the new method can produce an accurate and robust results.

Comparision of DdQm models in image optical flow analysis based on LBM

The optical flow analysis of the image sequence based on the formal lattice Boltzmann equation, with different DdQm models, is discussed in this paper. The Mgorithm is based on the lattice Boltzmann method （LBM）, which is used in computational fluid dynamics theory for the simulation of fluid dynamics. At first, a generalized approximation to the formal lattice Boltzmann equation is discussed. Then the effects of different DdQm models on the results of the optical flow estimation are compared with each other, while calculating the movement vectors of pixels in the image sequence. The experimental results show that the higher dimension DdQm models, e.g., D3Q15 are more effective than those lower dimension ones.

Optical flow-based method to estimate internal wave parameters from X-band marine radar images

The velocity and direction of internal waves(IWs) are important parameters of the ocean,however,traditional observation methods can only obtain the average parameters of IWs for a single location or large area.Herein,a new method based on optical flow is proposed to derive the phase velocity vectors of IWs from X-band marine radar images.First,the X-band marine radar image sequence is averaged,and ramp correction is used to reduce the attenuation of gray values with increasing radial range.Second,the average propagation direction of the IWs is determined using the two-dimensional Fourier transform of the radar images;two radial profiles along this direction are selected from two adjacent radar images;and then,the average phase velocity of the IWs is estimated from these radial profiles.Third,the averaged radar images are processed via histogram equalization and binarization to reduce the influence of noise on the radar images.Fourth,a weighting factor is determined using the average phase velocity of a reference point;the phase velocities on the wave crest of the IWs are subsequently estimated via the optical flow method.Finally,the proposed method is validated using X-band marine radar image sequences observed on an oil platform in the South China Sea,and the error of the phase velocity is calculated to be 0.000 3–0.073 8 m/s.The application conditions of the proposed method are also discussed using two different types of IW packets.