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Journal articles on the topic 'Lucas-Kanade Optical Flow Tracker'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Hosseinyalamdary, S., and A. Yilmaz. "Motion Vector Field Estimation Using Brightness Constancy Assumption and Epipolar Geometry Constraint." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 9–16. http://dx.doi.org/10.5194/isprsannals-ii-1-9-2014.

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In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas

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Mendes, L., A. J. M. Bernardino, and R. M. L. Ferreira. "Optical Flow Methods For Tracer-Based Imaging Techniques In Fluid Mechanics." Proceedings of the International Symposium on the Application of Laser and Imaging Techniques to Fluid Mechanics 20 (July 11, 2022): 1–11. http://dx.doi.org/10.55037/lxlaser.20th.181.

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This paper is aimed at assessing the performance of Optical Flow methods to estimate flow velocities from images designed for 2D Particle Image Velocimetry (PIV). A benchmark is proposed, based on synthetic tracer images associated to rotation- and deformation-dominated flow configurations. The investigated Optical Flow methods are Lucas-Kanade, Horn-Schunck and Farnebäck, combined them with the Liu-Shen method. The true values of the flow field (ground truth) are compared with the results of PIV and Optical Flow methods. Relative and absolute errors are computed for different combinations of

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Narayana, Asha, and Narasimhadhan Venkata. "Enhanced Median Flow Tracker Based on Photometric Correction for Videos with Abrupt Changing Illumination." International Arab Journal of Information Technology 17, no. 2 (2019): 264–71. http://dx.doi.org/10.34028/iajit/17/2/15.

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Object tracking is a fundamental task in video surveillance, human-computer interaction and activity analysis. One of the common challenges in visual object tracking is illumination variation. A large number of methods for tracking have been proposed over the recent years, and median flow tracker is one of them which can handle various challenges. Median flow tracker is designed to track an object using Lucas-Kanade optical flow method which is sensitive to illumination variation, hence fails when sudden illumination changes occur between the frames. In this paper, we propose an enhanced media

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Chermak, L., N. Aouf, and M. A. Richardson. "Scale robust IMU-assisted KLT for stereo visual odometry solution." Robotica 35, no. 9 (2016): 1864–87. http://dx.doi.org/10.1017/s0263574716000552.

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SUMMARYWe propose a novel stereo visual IMU-assisted (Inertial Measurement Unit) technique that extends to large inter-frame motion the use of KLT tracker (Kanade–Lucas–Tomasi). The constrained and coherent inter-frame motion acquired from the IMU is applied to detected features through homogenous transform using 3D geometry and stereoscopy properties. This predicts efficiently the projection of the optical flow in subsequent images. Accurate adaptive tracking windows limit tracking areas resulting in a minimum of lost features and also prevent tracking of dynamic objects. This new feature tra

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Tauro, Flavia, Fabio Tosi, Stefano Mattoccia, Elena Toth, Rodolfo Piscopia, and Salvatore Grimaldi. "Optical Tracking Velocimetry (OTV): Leveraging Optical Flow and Trajectory-Based Filtering for Surface Streamflow Observations." Remote Sensing 10, no. 12 (2018): 2010. http://dx.doi.org/10.3390/rs10122010.

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Nonintrusive image-based methods have the potential to advance hydrological streamflow observations by providing spatially distributed data at high temporal resolution. Due to their simplicity, correlation-based approaches have until recent been preferred to alternative image-based approaches, such as optical flow, for camera-based surface flow velocity estimate. In this work, we introduce a novel optical flow scheme, optical tracking velocimetry (OTV), that entails automated feature detection, tracking through the differential sparse Lucas-Kanade algorithm, and then a posteriori filtering to

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Mendes, Luís P. N., Ana M. C. Ricardo, Alexandre J. M. Bernardino, and Rui M. L. Ferreira. "A Hybrid PIV/Optical Flow Method for Incompressible Turbulent Flows." Water 16, no. 7 (2024): 1021. http://dx.doi.org/10.3390/w16071021.

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We present novel velocimetry algorithms based on the hybridization of correlation-based Particle Image Velocimetry (PIV) and a combination of Lucas–Kanade and Liu–Shen optical flow (OpF) methods. An efficient Aparapi/OpenCL implementation of those methods is also provided in the accompanying open-source QuickLabPIV-ng tool enabled with a Graphical User Interface (GUI). Two different options of hybridization were developed and tested: OpF as a last step, after correlation-based PIV, and OpF as a substitute for sub-pixel interpolation. Hybridization increases the spatial resolution of PIV, enabl

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Nugroho, G. A., Syahrul, E. Maryadi, et al. "Rain Scanner Radar and Optical Flow Combination For Early Identification of The Incoming Bow Echo Heavy Precipitation." IOP Conference Series: Earth and Environmental Science 1245, no. 1 (2023): 012031. http://dx.doi.org/10.1088/1755-1315/1245/1/012031.

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Abstract In this study, heavy precipitation in the form of bow echo is observed, identified, and tracked using a rain scanner and optical flow method. Two case studies of bow echoes with a range of properties from 15 to 33 km were observed in the afternoon on 1st February and 4th February 2021. The rain scanner developed based on X-band radar could obtain the first detection of the bow echo shape. The difference between these two bow echoes events is from their initiation. The first bow echo cases are initiated from weakly organized cells. Meanwhile, the second case of bow echo is initiated fr

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Eicken, Hajo, Joshua Jones, Franz Meyer, et al. "Environmental Security in Arctic Ice-Covered Seas: From Strategy to Tactics of Hazard Identification and Emergency Response." Marine Technology Society Journal 45, no. 3 (2011): 37–48. http://dx.doi.org/10.4031/mtsj.45.3.1.

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AbstractEnvironmental change and increasing industrial activity in the maritime Arctic require strategies to adapt to change and ensure safe operations. This problem has been defined at the broader strategic level. We evaluate key aspects of environmental security in ice-covered waters, focusing on tactical and operational information needs, which have received less attention. Monitoring of environmental hazards and effective emergency response in sea ice environments require high-resolution data of ice hazard distributions (e.g., multiyear ice, landfast ice breakout, and ice push events), ice

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Regev, Nir, and Dov Wulich. "Multi-Modal, Remote Breathing Monitor." Sensors 20, no. 4 (2020): 1229. http://dx.doi.org/10.3390/s20041229.

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Monitoring breathing is important for a plethora of applications including, but not limited to, baby monitoring, sleep monitoring, and elderly care. This paper presents a way to fuse both vision-based and RF-based modalities for the task of estimating the breathing rate of a human. The modalities used are the F200 Intel® RealSenseTM RGB and depth (RGBD) sensor, and an ultra-wideband (UWB) radar. RGB image-based features and their corresponding image coordinates are detected on the human body and are tracked using the famous optical flow algorithm of Lucas and Kanade. The depth at these coordin

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M., Murugappan, and Mutawa A. "Facial geometric feature extraction based emotional expression classification using machine learning algorithms." PLOS ONE 16, no. 2 (2021): e0247131. http://dx.doi.org/10.1371/journal.pone.0247131.

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Emotion plays a significant role in interpersonal communication and also improving social life. In recent years, facial emotion recognition is highly adopted in developing human-computer interfaces (HCI) and humanoid robots. In this work, a triangulation method for extracting a novel set of geometric features is proposed to classify six emotional expressions (sadness, anger, fear, surprise, disgust, and happiness) using computer-generated markers. The subject’s face is recognized by using Haar-like features. A mathematical model has been applied to positions of eight virtual markers in a defin

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Fue, Kadeghe G., Wesley M. Porter, Edward M. Barnes, and Glen C. Rains. "Ensemble Method of Deep Learning, Color Segmentation, and Image Transformation to Track, Localize, and Count Cotton Bolls Using a Moving Camera in Real-Time." Transactions of the ASABE 64, no. 1 (2021): 341–52. http://dx.doi.org/10.13031/trans.13112.

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HighlightsAn ensemble method using color segmentation, deep learning, and image transformation was developed.Experiments were conducted to compare the method with other state-of-the-art tracking algorithms.The optimized ensemble method to track bolls achieved 94.4% accuracy using weakly trained tiny YOLOv2 models.The method achieved 7.6 frames per second and outperformed five other tracking methods.Abstract. In robotic applications, good perception can be computationally costly and create undesirable latency before a control decision is initiated. Most of the methods available for object detec

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Patel, Dhara, and Saurabh Upadhyay. "Optical Flow Measurement using Lucas Kanade Method." International Journal of Computer Applications 61, no. 10 (2013): 6–10. http://dx.doi.org/10.5120/9962-4611.

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Lee, Cho, Lee, and Whang. "Vision-Based Measurement of Heart Rate from Ballistocardiographic Head Movements Using Unsupervised Clustering." Sensors 19, no. 15 (2019): 3263. http://dx.doi.org/10.3390/s19153263.

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Heart rate has been measured comfortably using a camera without the skin-contact by the development of vision-based measurement. Despite the potential of the vision-based measurement, it has still presented limited ability due to the noise of illumination variance and motion artifacts. Remote ballistocardiography (BCG) was used to estimate heart rate from the ballistocardiographic head movements generated by the flow of blood through the carotid arteries. It was robust to illumination variance but still limited in the motion artifacts such as facial expressions and voluntary head motions. Rece

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Ibrahim, Furkan Ince, Socarras-Garzon Manuel, and Yang Tae-Cheon. "Hand Mouse: Real Time Hand Motion Detection System Based on Analysis of Finger Blobs." International Journal of Digital Content Technology and its Applications (JDCTA) 4, no. 2 (2010): 40–56. https://doi.org/10.4156/jdcta.vol4.issue2.5.

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Hand detection is a fundamental step in many practical applications as gesture recognition, video surveillance, and multimodal machine interface and so on. The aim of this paper is to present the methodology for hand detection and propose the hand motion detection method. Skin color is used to segment the hand region from background and hand blob is extracted from the segmented finger blobs. Analysis of finger blobs gives us the location of hand even when hand and head blobs are visible in the same image. In this paper, we propose a fast, computationally inexpensive so

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Ghalenoei, E., M. A. Sharifi, and M. Hasanlou. "Investigation of Optical Flow Techniques for Extracting Non-Rigid Sea Surface Currents." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2/W3 (October 22, 2014): 121–26. http://dx.doi.org/10.5194/isprsarchives-xl-2-w3-121-2014.

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This paper is about performance evaluation of two optical flow (OF) methods for extracting sea surface curved motions like eddies. By incorporating a simple matrix and its rotation in programming procedure, curved motion can be obtained. These two OF methods are Horn/Schunk and Lucas/Kanade. The Horn/Schunk method depends on a smoothness parameter (α) and when it changes, smoothness and reality change too. The Lucas/Kanade method is more complex than previous one. It depends on two parameters, smoothness parameter (Sigma) and window size (Win). Different values for Win and Sigma change smoothn

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Sharmin, Nusrat, and Remus Brad. "Optimal Filter Estimation for Lucas-Kanade Optical Flow." Sensors 12, no. 9 (2012): 12694–709. http://dx.doi.org/10.3390/s120912694.

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Svitlana, Maksymova, Yevsieiev Vladyslav, and Alkhalaileh Ahmad. "THE LUCAS-KANADE METHOD IMPLEMENTATION FOR ESTIMATING THE OBJECTS MOVEMENT IN THE MOBILE ROBOT'S WORKSPACE." Journal of Universal Science Research 2, no. 3 (2024): 187–97. https://doi.org/10.5281/zenodo.10841784.

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This article presents the Lucas-Kanade method implementation for estimating the objects movement in the mobile robot’s workspace using the Python programming language. The Lucas-Kanade method is used to calculate optical flow from sequential images and allows the motion of objects to be estimated. The necessary mathematical expressions are considered. As part of the study, experiments were conducted with different lighting levels to evaluate the robotic ability of the method under changing lighting conditions.

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Al-Qudah, Saleh, and Mijia Yang. "Large Displacement Detection Using Improved Lucas–Kanade Optical Flow." Sensors 23, no. 6 (2023): 3152. http://dx.doi.org/10.3390/s23063152.

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Displacement is critical when it comes to the evaluation of civil structures. Large displacement can be dangerous. There are many methods that can be used to monitor structural displacements, but every method has its benefits and limitations. Lucas–Kanade (LK) optical flow is recognized as a superior computer vision displacement tracking method, but it only applies to small displacement monitoring. An upgraded LK optical flow method is developed in this study and used to detect large displacement motions. One motion controlled by a multiple purpose testing system (MTS) and a free-falling exper

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Kusuma, Muh Nur Risyad Rais Rafsanjani Hadi, and Danang Aditya Nugraha. "Powerpoint Kontrol dengan Gesture Detection Menggunakan Metode Optical Flow Lucas-Kanade." RAINSTEK: Jurnal Terapan Sains dan Teknologi 7, no. 1 (2025): 27–36. https://doi.org/10.21067/jtst.v7i1.10835.

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Penggunaan peralatan seperti keyboard, mouse perlu membutuhkankontak fisik untuk melakukan kontrol terutama pada aktivitas pembelajaran di kelas.Salah satu pada implementasi penelitian ini menggunakan teknologi computer visionyaitu untuk deteksi gesture tangan yang mampu mengontrol slide pada softwarepowerpoint. Sehingga presentator dapat melakukan presentasi tanpa harus ada kontaklangsung dengan perangkat laptop. Metode yang digunakan untuk proses deteksigesture tangan yaitu OpticalFlow Lucas-Kanade, metode ini digunakan untukmendeteksi pola pergerakan objek gambar antara dua frame berturut-t

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Carlos, Frins, Lestari Margatama, and Indra Riyanto. "Perancangan Sistem Deteksi Kecepatan Kendaraan Dengan Metode Optical Flow." Jurnal Ticom: Technology of Information and Communication 10, no. 1 (2021): 56–63. http://dx.doi.org/10.70309/ticom.v10i1.18.

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Tingkat kesadaran pengendara kendaraan bermotor dalam mengendalikan kecepatan secara umum masih rendah, hal ini terlihat dari masih tingginya pelanggaran batas kecepatan laju kendaraan terutama ketika di jalan bebas hambatan. Kondisi tersebut bisa membahayakan keselamatan diri pengendara dan pengendara lain sehingga diperlukan upaya penertiban. Sebagai pendukung upaya tersebut, pada tugas akhir ini akan merancang sistem pendeteksi kecepatan menggunakan metode optical flow dengan algoritma Lucas Kanade. Optical flow adalah perkiraan gerakan suatu bagian dari sebuah citra berdasarkan turunan int

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Zhang, Xiaoli, Punan Li, and Yibing Li. "Feature Point Extraction and Motion Tracking of Cardiac Color Ultrasound under Improved Lucas–Kanade Algorithm." Journal of Healthcare Engineering 2021 (August 3, 2021): 1–10. http://dx.doi.org/10.1155/2021/4959727.

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The purpose of this research is to study the application effect of Lucas–Kanade algorithm in right ventricular color Doppler ultrasound feature point extraction and motion tracking under the condition of scale invariant feature transform (SIFT). This study took the right ventricle as an example to analyze the extraction effect and calculation rate of SIFT algorithm and improved Lucas–Kanade algorithm. It was found that the calculation time before and after noise removal by the SIFT algorithm was 0.49 s and 0.46 s, respectively, and the number of extracted feature points was 703 and 698, respec

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Peng, Yahui, Xiaochen Liu, Chong Shen, et al. "An Improved Optical Flow Algorithm Based on Mask-R-CNN and K-Means for Velocity Calculation." Applied Sciences 9, no. 14 (2019): 2808. http://dx.doi.org/10.3390/app9142808.

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Aiming at enhancing the accuracy and reliability of velocity calculation in vision navigation, an improved method is proposed in this paper. The method integrates Mask-R-CNN (Mask Region-based Convolutional Neural Network) and K-Means with the pyramid Lucas Kanade algorithm in order to reduce the harmful effect of moving objects on velocity calculation. Firstly, Mask-R-CNN is used to recognize the objects which have motions relative to the ground and covers them with masks to enhance the similarity between pixels and to reduce the impacts of the noisy moving pixels. Then, the pyramid Lucas Kan

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Han, Zhao Hui, and Yan Feng Wang. "Application of L-K Optical Flow Algorithm Mixed with Pyramid on Calculating Water Surface Flow Field." Applied Mechanics and Materials 333-335 (July 2013): 897–903. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.897.

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A classical Lucas-Kanade optical flow algorithm was used to analysis the IR Image sequence of the wind-driven surface in this paper. Gaussian pyramid representation was introduced to retain both detail components and veracity for velocity field when considering the aperture problem and robustness. Three layers of pyramid for L-K optical flow is the best comparing with other layers (from one to four) in property. L-K optical flow algorithm mixed with pyramid representation shown an qualified power on calculating water surface flow field, demonstrated by optical flow fields on different wind spe

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Chen, Lei, Hua Yang, Takeshi Takaki, and Idaku Ishii. "Real-Time Optical Flow Estimation Using Multiple Frame-Straddling Intervals." Journal of Robotics and Mechatronics 24, no. 4 (2012): 686–98. http://dx.doi.org/10.20965/jrm.2012.p0686.

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In this paper, we propose a novel method for accurate optical flow estimation in real time for both high-speed and low-speed moving objects based on High-Frame-Rate (HFR) videos. We introduce a multiframe-straddling function to select several pairs of images with different frame intervals from an HFR image sequence even when the estimated optical flow is required to output at standard video rates (NTSC at 30 fps and PAL at 25 fps). The multiframestraddling function can remarkably improve the measurable range of velocities in optical flow estimation without heavy computation by adaptively selec

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Li, Ling, Zhengwei He, Sheng Chen, et al. "Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas–Kanade Optical Flow Technique." Atmosphere 9, no. 7 (2018): 260. http://dx.doi.org/10.3390/atmos9070260.

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Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas–Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on the subpixel level by using the optical flow technique and then extrapolates the precipitation using a linear method through redistribution and interpolation. The SPLK compares with object-based and pixel-based nowcasting algorithms using eight thunderstor

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Mahalingam, Venkataraman, Koustav Bhattacharya, Nagarajan Ranganathan, Hari Chakravarthula, Robin Roberson Murphy, and Kevin Sheldon Pratt. "A VLSI Architecture and Algorithm for Lucas–Kanade-Based Optical Flow Computation." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 18, no. 1 (2010): 29–38. http://dx.doi.org/10.1109/tvlsi.2008.2006900.

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Plyer, Aurélien, Guy Le Besnerais, and Frédéric Champagnat. "Massively parallel Lucas Kanade optical flow for real-time video processing applications." Journal of Real-Time Image Processing 11, no. 4 (2014): 713–30. http://dx.doi.org/10.1007/s11554-014-0423-0.

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Zainal, Zairulazha, Rizauddin Ramli, and Mohd Marzuki Mustafa. "Optical Flow Vectors Thresholding in Assisting Heading Direction Estimation." Applied Mechanics and Materials 393 (September 2013): 623–28. http://dx.doi.org/10.4028/www.scientific.net/amm.393.623.

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This paper presents a technique on how to estimate heading direction of a moving vision system such as mobile robot. The heading direction is represented by estimation angle which is generated by optical flow vectors threshold technique (OFVTT). The utilizations of optical flow field generated based on Horn-Schunck and Lucas-Kanade methods are essential in order to compute the threshold value. The performance of the proposed technique was determined through percentage of root mean square error (RMSE). Based on our experimental results, it can be ascertained that combination of Horn-Schunck met

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Yordanov, V., X. Q. Truong, M. Corti, L. Longoni, and M. A. Brovelli. "APPLICATION OF LUCAS-KANADE DENSE FLOW FOR TERRAIN MOTION IN LANDSLIDE MONITORING APPLICATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 1089–96. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-1089-2023.

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Abstract. Landslides are natural hazards that can cause severe damage and loss of life. Optical cameras are a low-cost and high-resolution alternative among many monitoring systems, as their size and capabilities can vary, allowing for flexible implementation and location. Computer vision is a branch of artificial intelligence that can analyze and understand optical images, using techniques such as optical flow, image correlation and machine learning. The application of such techniques can estimate the motion vectors, displacement fields, providing valuable information for landslide detection,

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Wang, Yan Ni. "A Local Optical Flow Constraint Target Extracting Algorithm of Kalman Filter Based on Background Modeling." Applied Mechanics and Materials 596 (July 2014): 316–21. http://dx.doi.org/10.4028/www.scientific.net/amm.596.316.

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Owing to the problems of inter frame difference method cannot extract the entire target and most optical flow algorithms with computational time, poor real-time performance, a local optical flow constraint target extracting algorithm of Kalman filter based on background modeling is proposed. Firstly use Kalman filter method based on background modeling predict and update the background, then make Lucas-Kanade local optical flow algorithm search the background changing region, finally determine the gray contour, extract target. Compared with the classical algorithms, the simulation results show

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Liu, Dong Ming, Chao Liu, and Hai Wei Mu. "Algorithm Optimization of Motion Tracking Based on Optical Flow." Advanced Materials Research 926-930 (May 2014): 2938–41. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.2938.

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Optical flow is an important kind of video motion tracking algorithm, and Lucas-Kanade (LK) algorithm is an effective differential method in terms of calculating optical flow. The 3D Gaussian smoothing filter is properly introduced in the image preprocessing stage of the LK algorithm, which makes it possible to increase the correlation of the adjacent pixels in the time axis, improve the blur effect of the video image and overcome the 2D Gaussian filters disadvantage that is not suitable for the video image processing. More importantly, the optimized 3D non-Gaussian matching filter is chosen d

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Zhong, Lingjun, Limin Meng, Wei Hou, and Li Huang. "An Improved Visual Odometer Based on Lucas-Kanade Optical Flow and ORB Feature." IEEE Access 11 (2023): 47179–86. http://dx.doi.org/10.1109/access.2023.3274784.

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P, Sabelnikov, and Sabelnikov Yu. "Search for identical points in the inter-pixel space of video images." Artificial Intelligence 28, AI.2023.28(1)) (2023): 155–62. http://dx.doi.org/10.15407/jai2023.01.155.

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One of the ways to describe objects in images is to identify some of their characteristic points or points of attention. Areas surrounding attention points are described by descriptors (a set of features) in such a way that they can be identified and compared. On these features the search for identical points on other images is carried out by scanning them with a sliding window. The most famous descriptors and methods for finding identical points are: SIFT, SURF, GLOH, BRIEF and others. This group of methods is characterized by the fact that the displacement of identical points in video images

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Juan, Romero, Verdier Damien, Raffaitin Clement, Miguel Procel Luis, and Trojman Lionel. "Simple Hardware Implementation of Motion Estimation Algorithms." ACI Avances en Ciencias e Ingenierías 11, no. 3 (2019): 12. https://doi.org/10.18272/aci.v11i3.1352.

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We present in the following work a hardware implementation of the two principal optical flow methods. The work is based on the methods developed by Lucas & Kanade, and Horn & Schunck. The implementation is made by using a field programmable gate array and Hardware Description Language. To achieve a successful implementation, the algorithms were optimized. The results show the optical flow as a vector field over one frame, which enable an easy detection of the movement. The results are compared to a software implementation to insure the success of the method. The implementation is a fas

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Wang, Guoyin, Yong Yang, and Kun He. "A Robust Facial Feature Tracking Method Based on Optical Flow and Prior Measurement." International Journal of Cognitive Informatics and Natural Intelligence 4, no. 4 (2010): 62–75. http://dx.doi.org/10.4018/jcini.2010100105.

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Cognitive informatics (CI) is a research area including some interdisciplinary topics. Visual tracking is not only an important topic in CI, but also a hot topic in computer vision and facial expression recognition. In this paper, a novel and robust facial feature tracking method is proposed, in which Kanade-Lucas-Tomasi (KLT) optical flow is taken as basis. The prior method of measurement consisting of pupils detecting features restriction and errors and is used to improve the predictions. Simulation experiment results show that the proposed method is superior to the traditional optical flow

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Ammar, Anis, Hana Ben Fredj, and Chokri Souani. "Accurate Realtime Motion Estimation Using Optical Flow on an Embedded System." Electronics 10, no. 17 (2021): 2164. http://dx.doi.org/10.3390/electronics10172164.

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Motion estimation has become one of the most important techniques used in realtime computer vision application. There are several algorithms to estimate object motions. One of the most widespread techniques consists of calculating the apparent velocity field observed between two successive images of the same scene, known as the optical flow. However, the high accuracy of dense optical flow estimation is costly in run time. In this context, we designed an accurate motion estimation system based on the calculation of the optical flow of a moving object using the Lucas–Kanade algorithm. Our appro

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Zhu, Wei, Li Tian, Fang Di, Jian Li Li, and Ke Jie Li. "Dynamic Targets Detection for Robotic Applications Using Panoramic Camera Based on Optical Flow." Applied Mechanics and Materials 376 (August 2013): 455–60. http://dx.doi.org/10.4028/www.scientific.net/amm.376.455.

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Optical flow method is an important and valid method in the field of detection and tracking of moving objects for robot inspection system. Due to the traditional Horn-Schunck optical flow method and Lucas-Kanade optical flow method cannot meet the demands of real-time and accuracy simultaneously, an improved optical flow method based on Gaussian image pyramid is proposed. The layered structure of the images can be obtained by desampling of the original sequential images so that the motion with the high speed can be changed into continuous motion with lower speed. Then the optical flows of corn

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R, Reeja S., and Dr N. P. Kavya. "A System for Movement Detecting Congestion." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 3 (2014): 4302–7. http://dx.doi.org/10.24297/ijct.v13i3.2761.

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In this paper, we present a system for tracking and provide early information of hazardous locationsin huge gatherings. It is based on optic flow estimations and detects sequences of crowd motion that are characteristic for devastating congestions. For optic flow computation, Lucas- Kanade method is employed to determine the optical flow vectors for the gathered video. Segmentation of video sequences is done and optic flow is determined for respective segments. A threshold optic flow is chosen in such a way that the tracking of congested area in video is easilydoneby comparing it with respecti

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Wang, Xianlun, Yusong Zhou, Gongxing Yu, and Yuxia Cui. "A Lightweight Visual Odometry Based on LK Optical Flow Tracking." Applied Sciences 13, no. 20 (2023): 11322. http://dx.doi.org/10.3390/app132011322.

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Autonomous mobile robots (AMRs) require SLAM technology for positioning and mapping. Their accuracy and real-time performance are the keys to ensuring that the robot can safely and accurately complete the driving task. The visual SLAM systems based on feature points have high accuracy and robustness but poor real-time performance. A lightweight Visual Odometry (VO) based on Lucas–Kanade (LK) optical flow tracking is proposed. Firstly, a robust key point matching relationship between adjacent images is established by using a uniform motion model and a pyramid-based sparse optical flow tracking

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Xu, Hong Ke, Chao Cai, Hao Chen, Jian Wu Fang, and Shu Guang Li. "Research on License Plate Tracking and Detection Based on Optical Flow." Applied Mechanics and Materials 135-136 (October 2011): 775–80. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.775.

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Aiming at regulating the toll evasion behaviors in highway weight charges and reducing charge disputes caused by jumping, this article studied the algorithm that tracks vehicle beating when it is passing the scale. Based on license plate location, vehicle movement could be characterized by tracking the plate centroid using Lucas-Kanade optical flow algorithm. The optical flow vector of the centroid was calculated frame by frame, which could be used for drawing trajectory of centroid coordinates, and calculating beating parameters. In order to expand the detection range and adaptability of the

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Seong, Han-Soo, Chae Eun Rhee, and Hyuk-Jae Lee. "A Novel Hardware Architecture of the Lucas–Kanade Optical Flow for Reduced Frame Memory Access." IEEE Transactions on Circuits and Systems for Video Technology 26, no. 6 (2016): 1187–99. http://dx.doi.org/10.1109/tcsvt.2015.2437077.

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Mella, DA, W. Brevis, JE Higham, V. Racic, and L. Susmel. "Image-based tracking technique assessment and application to a fluid–structure interaction experiment." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 16 (2019): 5724–34. http://dx.doi.org/10.1177/0954406219853852.

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This work analyses the accuracy and capabilities of two image-based tracking techniques related to digital image correlation and the Lucas–Kanade optical flow method, with the subsequent quantification of body motion in a fluid–structure interaction experiment. A computer-controlled shaker was used as a benchmark case to create a one-dimensional oscillatory target motion. Three target frequencies were recorded. The measurements obtained with a low-cost digital camera were compared to a high-precision motion tracking system. The comparison was performed under changes in image resolution, target

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Chigrinskiy, V. V., and I. A. Matveev. "ACCURACY ESTIMATION OF THE OPTICAL FLOWMETHODS IN THE IRIS STRUCTURE MOTION ANALYSIS VIA CONTROLLED DEFORMATIONS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W4 (May 10, 2017): 163–67. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w4-163-2017.

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The iris structure motion is analyzed. Extension and compression of the iris structural elements are nonlinear with respect to the pupil radius change. To reveal this nonlinearity the Lucas-Kanade, Horn-Schunck and modified Horn-Chunck optical flow methods are used. To aim is to estimate the accuracies of these methods. To solve the problem an implementation of the methods on the synthetic data is proposed. The data are obtained by applying deformations, which correspond to the certain models, to the eye images. The results of the methods implementation are compared with the used models and th

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Guo, Guangzhi, Zuoxiao Dai, and Yuanfeng Dai. "Real-Time Stereo Visual Odometry Based on an Improved KLT Method." Applied Sciences 12, no. 23 (2022): 12124. http://dx.doi.org/10.3390/app122312124.

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Real-time stereo visual odometry (SVO) localization is a challenging problem, especially for a mobile platform without parallel computing capability. A possible solution is to reduce the computational complexity of SVO using a Kanade–Lucas–Tomasi (KLT) feature tracker. However, the standard KLT is susceptible to scale distortion and affine transformation. Therefore, this work presents a novel SVO algorithm yielding robust and real-time localization based on an improved KLT method. First, in order to improve real-time performance, feature inheritance is applied to avoid time-consuming feature d

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Winkler, Joab R. "Error Analysis and Condition Estimation of the Pyramidal Form of the Lucas-Kanade Method in Optical Flow." Electronics 13, no. 5 (2024): 812. http://dx.doi.org/10.3390/electronics13050812.

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Optical flow is the apparent motion of the brightness patterns in an image. The pyramidal form of the Lucas-Kanade (LK) method is frequently used for its computation but experiments have shown that the method has deficiencies. Problems arise because of numerical issues in the least squares (LS) problem minAx−b22, A∈Rm×2 and m≫2, which must be solved many times. Numerical properties of the solution x0=A†b = (ATA)−1ATb of the LS problem are considered and it is shown that the property m≫2 has implications for the error and stability of x0. In particular, it can be assumed that b has components t

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Yang, Xinghai, Fengjiao Wang, Zhiquan Bai, Feifei Xun, Yulin Zhang, and Xiuyang Zhao. "Deep Learning-Based Congestion Detection at Urban Intersections." Sensors 21, no. 6 (2021): 2052. http://dx.doi.org/10.3390/s21062052.

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In this paper, a deep learning-based traffic state discrimination method is proposed to detect traffic congestion at urban intersections. The detection algorithm includes two parts, global speed detection and a traffic state discrimination algorithm. Firstly, the region of interest (ROI) is selected as the road intersection from the input image of the You Only Look Once (YOLO) v3 object detection algorithm for vehicle target detection. The Lucas-Kanade (LK) optical flow method is employed to calculate the vehicle speed. Then, the corresponding intersection state can be obtained based on the ve

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Nguyen, Tran Xuan Bach, Kent Rosser, and Javaan Chahl. "A Comparison of Dense and Sparse Optical Flow Techniques for Low-Resolution Aerial Thermal Imagery." Journal of Imaging 8, no. 4 (2022): 116. http://dx.doi.org/10.3390/jimaging8040116.

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It is necessary to establish the relative performance of established optical flow approaches in airborne scenarios with thermal cameras. This study investigated the performance of a dense optical flow algorithm on 14 bit radiometric images of the ground. While sparse techniques that rely on feature matching techniques perform very well with airborne thermal data in high-contrast thermal conditions, these techniques suffer in low-contrast scenes, where there are fewer detectable and distinct features in the image. On the other hand, some dense optical flow algorithms are highly amenable to para

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GHOUL, K., S. ZAIDI, and Z. LABOUDI. "A New Motion Estimation Method using Modified Hexagonal Search Algorithm and Lucas-Kanade Optical Flow Technique." Advances in Electrical and Computer Engineering 24, no. 1 (2024): 33–40. http://dx.doi.org/10.4316/aece.2024.01004.

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Liu, Yu, Du-Gang Xi, Zhao-Liang Li, and Yang Hong. "A new methodology for pixel-quantitative precipitation nowcasting using a pyramid Lucas Kanade optical flow approach." Journal of Hydrology 529 (October 2015): 354–64. http://dx.doi.org/10.1016/j.jhydrol.2015.07.042.

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Marzban, Caren, and Scott Sandgathe. "Optical Flow for Verification." Weather and Forecasting 25, no. 5 (2010): 1479–94. http://dx.doi.org/10.1175/2010waf2222351.1.

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Abstract Modern numerical weather prediction (NWP) models produce forecasts that are gridded spatial fields. Digital images can also be viewed as gridded spatial fields, and as such, techniques from image analysis can be employed to address the problem of verification of NWP forecasts. One technique for estimating how images change temporally is called optical flow, where it is assumed that temporal changes in images (e.g., in a video) can be represented as a fluid flowing in some manner. Multiple realizations of the general idea have already been employed in verification problems as well as i

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