Relevant bibliographies by topics / Lucas-Kanade algoritmus

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Academic literature on the topic 'Lucas-Kanade algoritmus'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Lucas-Kanade algoritmus"

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Supriyatin, Wahyu. "ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE." Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika 17, no. 2 (July 14, 2020): 362–71. http://dx.doi.org/10.33751/komputasi.v17i2.2146.

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Object tracking one of computer vision. Computer vision similar to human eye function. The difficulty is to detect presence an object and object tracking application made. Object tracking used in aircraft, track cars, human body detectors at airports, a regulator the number of vehicles pass and navigation tools on robots. This study is to identify objects that pass in frame. This research also count the number of objects that pass in one frame. Object tracking done by comparing two algorithms namely Horn-Schunck and Lucas-Kanade. Both algorithms tested using the Source Block Parameter and Function Block Parameter. The test carried out with video resolution 120x160 and the position camera is 2-4 m. The object tracking test is conducted in the duration of 110-120 seconds. Stages tracking object was thresholding, filtering and region successfully obtain object binary video. The Lucas-Kanade has faster in identifying objects compared to the Horn-Schunck algorithm.
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Aashish, Kamath, and A. Vijayalakshmi. "Comparison of Viola-Jones And Kanade-Lucas-Tomasi Face Detection Algorithms." Oriental journal of computer science and technology 10, no. 1 (March 9, 2017): 151–59. http://dx.doi.org/10.13005/ojcst/10.01.20.

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Face detection technologies are used in a large variety of applications like advertising, entertainment, video coding, digital cameras, CCTV surveillance and even in military use. It is especially crucial in face recognition systems. You can’t recognise faces that you can’t detect, right? But a single face detection algorithm won’t work in the same way in every situation. It all comes down to how the algorithm works. For example, the Kanade-Lucas-Tomasi algorithm makes use of spatial common intensity transformation to direct the deep search for the position that shows the best match. It is much faster than other traditional techniques for checking far fewer potential matches between pictures. Similarly, another common face detection algorithm is the Viola-Jones algorithm that is the most widely used face detection algorithm. It is used in most digital cameras and mobile phones to detect faces. It uses cascades to detect edges like the nose, the ears etc. However, if there is a group of people and their faces are close to each other, the algorithm might not work that well as edges tend to overlap in a crowd. It might not detect individual faces. Therefore, in this work, we test both the Viola-Jones and the Kanade-Lucas-Tomasi algorithm for each image to find out which algorithm works best in which scenario.
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Hidayat, Nanda Maulana. "Aplikasi Augmented Reality Perlengkapan Militer Menggunakan Algoritma FAST Corner Dan Lucas Kanade." JATISI (Jurnal Teknik Informatika dan Sistem Informasi) 8, no. 3 (September 14, 2021): 1417–28. http://dx.doi.org/10.35957/jatisi.v8i3.1060.

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Pengetahuan mengenai perlengkapan kemiliteran tidak hanya diperoleh melalui pameran saja, dengan adanya perkembangan teknologi informasi bisa diperoleh melalui aplikasi. Penggunaan aplikasi augmented reality dapat dijadikan contoh dalam pengetahuan perlengkapan militer secara tiga dimensi. Perancangan ini bertujuan memberikan pengetahuan kepada masyarakat umum dengan menggunakan teknologi Augmented Reality. Perancangan ini menggunakan metode ADDIE dan algoritma FAST Corner dan Lucas Kanade. Perancangan ini menghasilkan sebuah aplikasi yang berisi pengenalan perlengkapan militer yang terdiri dari baret, topi boonie, topi patroli, helm, kacamata, tas besar, P3K (Pertolongan Pertama Pada kecelakaan), pisau, senjata jauh dan senjata menengah. Informasi singkat mengenai masing-masing perlengkapan militer yang dirancang secara menarik agar masyarakat umum mudah memahami dalam menggunakan aplikasi yang dapat dijalankan pada platform Android.
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Li, Ling, Zhengwei He, Sheng Chen, Xiongfa Mai, Asi Zhang, Baoqing Hu, Zhi Li, and Xinhua Tong. "Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas–Kanade Optical Flow Technique." Atmosphere 9, no. 7 (July 12, 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 thunderstorm events to assess its performance. The results suggest that the SPLK can perform better nowcasting of precipitation than the object-based and pixel-based algorithms with higher adequacy in tracking and predicting severe storms in 0–2 h lead-time forecasting.
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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, respectively. The number of feature points extracted by the SIFT algorithm and the calculation time were significantly better than those of other algorithms ( P < 0.01 ). The mean logarithm of the matching points of the SIFT algorithm for order matching and reverse order matching was 20.54 and 20.46, respectively. The calculation time and the number of feature points for the SIFT speckle tracking method were 1198.85 s and 81, respectively, and those of the optical flow method were 3274.19 s and 80, respectively. The calculation time of the SIFT speckle tracking method was significantly lower than that of the optical flow method ( P < 0.05 ), and there was no statistical difference in the number of feature points between the SIFT speckle tracking method and the optical flow method ( P > 0.05 ). In conclusion, the improved Lucas–Kanade algorithm based on SIFT significantly improves the accuracy of feature extraction and motion tracking of color Doppler ultrasound, which shows the value of the algorithm in the clinical application of color Doppler ultrasound.
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EVANGELIDIS, GEORGIOS D., and EMMANOUIL Z. PSARAKIS. "AN ECC-BASED ITERATIVE ALGORITHM FOR PHOTOMETRIC INVARIANT PROJECTIVE REGISTRATION." International Journal on Artificial Intelligence Tools 18, no. 01 (February 2009): 121–39. http://dx.doi.org/10.1142/s021821300900007x.

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The ability of an algorithm to accurately estimate the parameters of the geometric transformation which aligns two image profiles even in the presence of photometric distortions can be considered as a basic requirement in many computer vision applications. Projective transformations constitute a general class which includes as special cases the affine, as well as the metric subclasses of transformations. In this paper the applicability of a recently proposed iterative algorithm, which uses the Enhanced Correlation Coefficient as a performance criterion, in the projective image registration problem is investigated. The main theoretical results concerning the proposed iterative algorithm are presented. Furthermore, the performance of the iterative algorithm in the presence of nonlinear photometric distortions is compared against the leading Lucas-Kanade algorithm and its simultaneous inverse compositional variant with the help of a series of experiments involving strong or weak geometric deformations, ideal and noisy conditions and even over-modelling of the warping process. Although under ideal conditions the proposed algorithm and simultaneous inverse compositional algorithm exhibit a similar performance and both outperform the Lucas-Kanade algorithm, under noisy conditions the proposed algorithm outperforms the other algorithms in convergence speed and accuracy, and exhibits robustness against photometric distortions.
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Lin, Yih-Lon. "Least Trimmed Squares Approach to Lucas-Kanade Algorithm in Object Tracking Problems." Mathematical Problems in Engineering 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/324824.

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The object tracking problem is an important research topic in computer vision. For real applications such as vehicle tracking and face tracking, there are many efficient and real-time algorithms. In this study, we will focus on the Lucas-Kanade (LK) algorithm for object tracking. Although this method is time consuming, it is effective in tracking accuracy and environment adaptation. In the standard LK method, the sum of squared errors is used as the cost function, while least trimmed squares is adopted as the cost function in this study. The resulting estimator is robust against outliers caused by noises and occlusions in the tracking process. Simulations are provided to show that the proposed algorithm outperforms the standard LK method in the sense that it is robust against the outliers in the object tracking problems.
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Rahmawati, Lailia. "Deteksi Abnormality Dengan Menggunakan Algortima KLT Pada Citra Video CCTV." Jurnal Intake : Jurnal Penelitian Ilmu Teknik dan Terapan 8, no. 2 (October 10, 2017): 67–72. http://dx.doi.org/10.32492/jintake.v8i2.693.

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Deteksi Abnormality pada citra video CCTV yang ditunjukan pada individu tertentu atau suatu objek tertentu dimana gerakan diangkap minoritas. Penggunaan Algoritma KLT (Kanade-Lucas-Tomasi) sebagai Algortima Tracing hasil video yang sudah dilakukan proses Spektral Residual yang bertujuan menghasilkan gerakan global yang mengalokasikan daerah yang menarik. Dari hasil perbandingan tersebut diketahui bahwa jumlah piksel pada deteksi bergerak lebih kecil dari deteksi yang tidak bergerak. Maka hasilnya adalah yang ,minoritas abnormal adalah ada objek yang bergerak sendiri dibandingkan dengan objek-objek yang lainnya
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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 that new algorithm can extract the moving object quickly and accurately, and has better robustness to the environment changes and target circuitous movement.
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Shen, Lu Rong, Xia Bin Dong, Rui Tao Lu, Yong Bin Zheng, and Xin Sheng Huang. "Robust Spatial-Color Feature with New Similarity Measure and Adaptive Template Update for Mean-Shift Tracking." Applied Mechanics and Materials 321-324 (June 2013): 1021–29. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1021.

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In this paper, we analyze the object tracking task of mean-shift algorithm. A spatial-color and similarity based mean-shift tracking algorithm is proposed. The spatial-color feature is used to replace the color histogram, and an enhanced algorithm is derived by adopting a new similarity measure. We also introduce Lucas-Kanade algorithm to design a template update strategy, propose a template update algorithm for mean-shift. Experimental results show that these two improved mean-shift tracking algorithms have high tracking accuracy and good robustness to the change of appearance of the object.
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Dissertations / Theses on the topic "Lucas-Kanade algoritmus"

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Bernátek, Pavel. "Vizualizace pulzu ve videozáznamu obličeje." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-242090.

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In the semestral thesis is given basic methods of non-contact measurement heart rate. There is explained Eulerian video magnification method deals with the visualization of the pulse in the videosequence of face. The semestral thesis describes algorithm Viola-Jones face detection in images and algorithm Kanade-Lucas-Tomasi for tracking faces in the videosequence. Part of the work includes design and realization of measurement. There is explained realization of the program and documented execution results, which are discussed. From the results it is designed to guide for optimal recording.
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Mezera, Lukáš. "Zlepšení rozlišení pro vícečetné snímky stejné scény." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237196.

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Úkolem této diplomové práce je navrhnout vlastní metodu pro zvýšení rozlišení v obraze scény, pokud je k dispozici více snímků dané scény. V teoretické části diplomové práce jsou jako nejlepší metody pro zvýšení rozlišení v obraze vybrány ty, které jsou založeny na principech zpracování signálu. Dále jsou popsány základní požadavky metod pro zvýšení rozlišení v obraze při přítomnosti více snímků stejné scény a jejich typická struktura. Následuje stručný přehled těchto metod a jejich vzájemné porovnání podle optimálních kritérií. Praktická část diplomové práce se zabývá samotným návrhem metody pro zvýšení rozlišení v obraze, pokud je k dispozici více snímků této scény. První navržená metoda je naimplementována a otestována. Při testování této metody je však  zjištěna její špatná funkčnost pro snímky scény s nízkým rozlišením, které vznikly vzájemnou rotací. Z toho důvodu je navržena vylepšená metoda pro zvýšení rozlišení v obraze. Tato metoda využívá při svém výpočtu robustních technik. Díky tomu je již vylepšená metoda nezávislá na rotaci mezi snímky scény s nízkým rozlišením. I tato metoda je řádně otestována a její výsledky jsou porovnány s výsledky první navržené metody pro zvýšení rozlišení v obraze. V porovnání výpočetních časů je lepší první navrhovaná metoda, avšak její výsledky pro obrazy obsahující rotace nejsou kvalitní. Oproti tomu pro obrazy, které vznikly pouze posunem při snímání scény, jsou tyto výsledky velice dobré. Vylepšená metoda je tedy využitelná zejména pro obrazy obsahující rotace. V závěru této práce je ještě navrženo jedno vylepšení, které by mohlo zlepšit výsledky druhé navrhnuté metody pro zvýšení rozlišení v obraze scény.
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Casero, Cañas Ramón. "Left ventricle functional analysis in 2D+t contrast echocardiography within an atlas-based deformable template model framework." Thesis, University of Oxford, 2008. http://ora.ox.ac.uk/objects/uuid:b17b3670-551d-4549-8f10-d977295c1857.

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This biomedical engineering thesis explores the opportunities and challenges of 2D+t contrast echocardiography for left ventricle functional analysis, both clinically and within a computer vision atlas-based deformable template model framework. A database was created for the experiments in this thesis, with 21 studies of contrast Dobutamine Stress Echo, in all 4 principal planes. The database includes clinical variables, human expert hand-traced myocardial contours and visual scoring. First the problem is studied from a clinical perspective. Quantification of endocardial global and local function using standard measures shows expected values and agreement with human expert visual scoring, but the results are less reliable for myocardial thickening. Next, the problem of segmenting the endocardium with a computer is posed in a standard landmark and atlas-based deformable template model framework. The underlying assumption is that these models can emulate human experts in terms of integrating previous knowledge about the anatomy and physiology with three sources of information from the image: texture, geometry and kinetics. Probabilistic atlases of contrast echocardiography are computed, while noting from histograms at selected anatomical locations that modelling texture with just mean intensity values may be too naive. Intensity analysis together with the clinical results above suggest that lack of external boundary definition may preclude this imaging technique for appropriate measuring of myocardial thickening, while endocardial boundary definition is appropriate for evaluation of wall motion. Geometry is presented in a Principal Component Analysis (PCA) context, highlighting issues about Gaussianity, the correlation and covariance matrices with respect to physiology, and analysing different measures of dimensionality. A popular extension of deformable models ---Active Appearance Models (AAMs)--- is then studied in depth. Contrary to common wisdom, it is contended that using a PCA texture space instead of a fixed atlas is detrimental to segmentation, and that PCA models are not convenient for texture modelling. To integrate kinetics, a novel spatio-temporal model of cardiac contours is proposed. The new explicit model does not require frame interpolation, and it is compared to previous implicit models in terms of approximation error when the shape vector changes from frame to frame or remains constant throughout the cardiac cycle. Finally, the 2D+t atlas-based deformable model segmentation problem is formulated and solved with a gradient descent approach. Experiments using the similarity transformation suggest that segmentation of the whole cardiac volume outperforms segmentation of individual frames. A relatively new approach ---the inverse compositional algorithm--- is shown to decrease running times of the classic Lucas-Kanade algorithm by a factor of 20 to 25, to values that are within real-time processing reach.
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Book chapters on the topic "Lucas-Kanade algoritmus"

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Mi, Yao, Prakash Kumar Bipin, and Rajeev Kumar Shah. "Using Lucas-Kanade Algorithms to Measure Human Movement." In Communications in Computer and Information Science, 118–30. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5992-7_10.

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Conference papers on the topic "Lucas-Kanade algoritmus"

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Ghandi, Bashir Mohammed, R. Nagarajan, and Hazry Desa. "Facial emotion detection using GPSO and Lucas-Kanade algorithms." In 2010 International Conference on Computer and Communication Engineering (ICCCE). IEEE, 2010. http://dx.doi.org/10.1109/iccce.2010.5556754.

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S. P. Bove, Márcio, Jés J. F. Cerqueira, and Eduardo F. Simas Filho. "Novelty Detection Applied in Recognition of Facial Expressions." In Congresso Brasileiro de Automática - 2020. sbabra, 2020. http://dx.doi.org/10.48011/asba.v2i1.1118.

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Esta pesquisa investiga a capacidade das redes Perceptron de Múltiplas Camadas (MLP) e Função de Base Radial (RBF) na tarefa de Detecção de Novidade (DN) no reconhecimento de expressões faciais usando recursos de vídeo. O conjunto de dados de vídeo utilizado é produzido por atores profissionais em estúdio com estados afetivos básicos do rosto humano. Os algoritmos Viola-Jones, Kanade-Lucas-Tomasi (KLT) e Análise de Componentes Principais (PCA) são usados na fase de pré-processamento para extrair atributos da face. Os resultados avaliam o desempenho das redes MLP e RBF na tarefa DN, usando novas expressões faciais compatíveis com as utilizadas na fase de treinamento e também examinam a capacidade das redes em DN usando as faces de atores nunca antes vistos pelas redes. Neste processo, as redes MLP e RBF têm uma precisão de 98% para tarefa de classificação, 68% e 98% para DN com dados semelhantes aos dados da fase de treinamento e 100% para DN com dados totalmente novos. Assim, este trabalho reúne métodos e técnicas aplicadas na DN utilizando Redes Neurais Artificiais (RNA), visando a produção de sistemas interativos de cognição no campo da computação afetiva, baseados em técnicas de Inteligência Artificial (IA) e Visão Computacional.
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Kesrarat, Darun, and Vorapoj Patanavijit. "Experimental study efficiency of robust models of Lucas-Kanade optical flow algorithms in the present of Non-Gaussian Noise." In 2012 4th International Conference on Knowledge and Smart Technology (KST). IEEE, 2012. http://dx.doi.org/10.1109/kst.2012.6287737.

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