Download or read book Optical Flow and Trajectory Estimation Methods written by Joel Gibson and published by Springer. This book was released on 2016-09-01 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief focuses on two main problems in the domain of optical flow and trajectory estimation: (i) The problem of finding convex optimization methods to apply sparsity to optical flow; and (ii) The problem of how to extend sparsity to improve trajectories in a computationally tractable way. Beginning with a review of optical flow fundamentals, it discusses the commonly used flow estimation strategies and the advantages or shortcomings of each. The brief also introduces the concepts associated with sparsity including dictionaries and low rank matrices. Next, it provides context for optical flow and trajectory methods including algorithms, data sets, and performance measurement. The second half of the brief covers sparse regularization of total variation optical flow and robust low rank trajectories. The authors describe a new approach that uses partially-overlapping patches to accelerate the calculation and is implemented in a coarse-to-fine strategy. Experimental results show that combining total variation and a sparse constraint from a learned dictionary is more effective than employing total variation alone. The brief is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to new researchers looking for cutting edge topics in optical flow as well as veterans of optical flow wishing to learn of the latest advances in multi-frame methods. /div
Download or read book Object Trajectory Estimation Using Optical Flow written by Shuo Liu and published by . This book was released on 2009 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Object trajectory tracking is an important topic in many different areas. It is widely used in robot technology, traffic, movie industry, and others. Optical flow is a useful method in the object tracking branch and it can calculate the motion of each pixel between two frames, and thus it provides a possible way to get the trajectory of objects. There are numerous papers describing the implementation of optical flow. Some results are acceptable, but in many projects, there are limitations. In most previous applications, because the camera is usually static, it is easy to apply optical flow to identify the moving targets in a scene and get their trajectories. When the camera moves, a global motion will be added to the local motion, which complicates the issue. In this thesis we use a combination of optical flow and image correlation to deal with this problem, and have good experimental results. For trajectory estimation, we incorporate a Kalman Filter with the optical flow. Not only can we smooth the motion history, but we can also estimate the motion into the next frame. The addition of a spatial-temporal filter improves the results in our later process.
Download or read book An Improved Optical Flow Estimation Method and Its Application to Vehicle Following written by Jaeryong Kim and published by . This book was released on 1993 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sparse and Low Rank Constraints on Optical Flow and Trajectories written by Joel Gibson and published by . This book was released on 2014 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation we apply sparse constraints to improve optical flow and trajectories. We apply sparsity in two ways. First, with 2-frame optical flow, we enforce a sparse representation of flow patches using a learned overcomplete dictionary. Second, we apply a low rank constraint to trajectories via robust coupling. We begin with a review of optical flow fundamentals. We discuss the commonly used flow estimation strategies and the advantages and shortcomings of each. We introduce the concepts associated with sparsity including dictionaries and low rank matrices. Next we study the related fields of multi-frame optical flow and trajectories. Since the beginning of modern optical flow estimation methods, multiple frames have been used in an effort to improve the computation of motion. We look at why most of these efforts have failed. More recently, researchers have stitched together sequences of optical flow fields to create trajectories. These trajectories are temporally coherent, a necessary property for virtually every real-world application of optical flow. New methods compute these trajectories directly using variational methods and low-rank constraints. We also identify the need for appropriate data sets and evaluation methods for this nascent field. Optical flow is an ill-posed underconstrained inverse problem. Many recent approaches use total variation (TV) to constrain the flow solution to satisfy color constancy. In our first results presented, we find that learning a 2D overcomplete dictionary from the total variation result and then enforcing a sparse constraint on the flow improves the result. A new technique using partially overlapping patches accelerates the calculation. This approach is implemented in a coarse-to-fine strategy. Our results show that combining total variation and a sparse constraint from a learned dictionary is more effective than total variation alone. In our second results we compute optical flow and trajectories from an image sequence. Sparsity in trajectories is measured by matrix rank. We introduce a low rank constraint of linear complexity using random subsampling of the data. We demonstrate that, by using a robust coupling with the low rank constraint, our approach outperforms baseline methods on general image sequences.
Download or read book Evaluation of Optical Flow Estimation Techniques Using Optical Flow Streams written by Michael Joseph Kotrlik and published by . This book was released on 1998 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical Flow Estimation Based on the Method of Vector space Projections written by Hongli Zhang and published by . This book was released on 1998 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book On the Simultaneous Estimation of Optical Flow and Object State written by Nicholas J. Bauer and published by . This book was released on 2008 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the enhancement of differential optical flow techniques. The framwork of differential optical flow has been built upon to improve object motion estimation within a video stream or image sequence. This augmentation comes in the form of a combined optical flow and object state estimation method (SEOS).
Download or read book A New Method for Estimating Optical Flow written by William F. Clocksin and published by . This book was released on 1997 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "Accurate and high density estimation of optical flow vectors in an image sequence is accomplished by a method that estimates the velocity distribution function for small overlapping regions of the image. Because the distribution is multimodal, the method can accurately estimate the change in velocity near motion contrast borders. Large spatiotemporal support without sacrificing spatial resolution is a feature of the method, so it is not necessary to smooth the resulting flow vectors in a subsequent operation, and there is a certain degree of resistance to aperture and aliasing effects. Spatial support also provides for the accurate estimation of long-range displacements, and subpixel accuracy is achieved by a simple weighted mean near the mode of the velocity distribution function. The method is demonstrated using image sequences obtained from the analysis of ceramic and metal materials under stress. The performance of the system under degenerate conditions is also analysed to provide insight into the behaviour of optical flow methods in general."
Download or read book Stereo Scene Flow for 3D Motion Analysis written by Andreas Wedel and published by Springer. This book was released on 2011-08-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents methods for estimating optical flow and scene flow motion with high accuracy, focusing on the practical application of these methods in camera-based driver assistance systems. Clearly and logically structured, the book builds from basic themes to more advanced concepts, culminating in the development of a novel, accurate and robust optic flow method. Features: reviews the major advances in motion estimation and motion analysis, and the latest progress of dense optical flow algorithms; investigates the use of residual images for optical flow; examines methods for deriving motion from stereo image sequences; analyses the error characteristics for motion variables, and derives scene flow metrics for movement likelihood and velocity; introduces a framework for scene flow-based moving object detection and segmentation; includes Appendices on data terms and quadratic optimization, and scene flow implementation using Euler-Lagrange equations, in addition to a helpful Glossary.
Download or read book Computer Vision ECCV 2010 written by Kostas Daniilidis and published by Springer Science & Business Media. This book was released on 2010-08-30 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six-volume set comprising LNCS volumes 6311 until 6313 constitutes the refereed proceedings of the 11th European Conference on Computer Vision, ECCV 2010, held in Heraklion, Crete, Greece, in September 2010. The 325 revised papers presented were carefully reviewed and selected from 1174 submissions. The papers are organized in topical sections on object and scene recognition; segmentation and grouping; face, gesture, biometrics; motion and tracking; statistical models and visual learning; matching, registration, alignment; computational imaging; multi-view geometry; image features; video and event characterization; shape representation and recognition; stereo; reflectance, illumination, color; medical image analysis.
Download or read book The Estimation of Optical Flow written by Joseph Kevin Kearney and published by . This book was released on 1983 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optic Flow Computation written by Ajit Singh and published by Institute of Electrical & Electronics Engineers(IEEE). This book was released on 1991 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A method for optical flow evaluation considering reliability estimation written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Muitos sistemas biológicos utilizam visão como forma primária de sensoriamento. Ao longo de milhões de anos de evolução, as diferentes espécies vêm demonstrando opotencial associado à capacidade de visão. A partir da década de 60, foram iniciados os primeiros estudos no sentido de proporcionar às máquinas esta forma de sensoriamento. A esta nova forma de sensoriamento dá-se o nome de Visão Computacional. Em Visão Computacional, muitos casos requerem a determinação de um campo vetorial que descreva os deslocamentos ocorridos entre dois quadros consecutivos de uma seqüência genérica de vídeo. A este campo vetorial dá-se o nome de Optical Flow (FluxoÓtico). A determinação do Optical Flow é ainda um problema sem solução. No presente trabalho, propõe-se um novo estimador estatístico para a determinação do Fluxo Ótico. Este estimador possui complexidade O(n) e associa um grau de confiabilidade a cada estimativa realizada. É aplicável a qualquer sinal digital (não apenas imagens ou vídeo, mas também a som, volume, etc) e vem demonstrando esultados muito promissores.
Download or read book Multilevel Optimization for Dense Motion Estimation UUM Press written by El Mostafa Kalmoun and published by UUM Press. This book was released on 2012-01-01 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph offers design for fast and reliable technique in the dense motion estimation. This Multilevel Optimization for Dense Motion Estimation work blends both theory and applications to equip reader with an understanding of basic concepts necessary to apply in solving dense motion in a sequence of images. Illustrating well-known variation models for dealing with optical flow estimation, this monograph introduces variation models with applications. A host of variation models are outlines such as Horn-Schunck model, Contrast Invariation Models and Models for Large Displacement. Special attention is also given to multilevel optimization techniques namely multiresolution and multigrid methods to improve the convergence of the global optimum when compared to using only one level resolution in the context of computer vision. This monograph is a robust resource that provides insightful introduction to the field of image processing with its theory and applications. Overall, Multilevel Optimization for Dense Motion Estimation is highly recommended for scientists and engineers for an excellent choice for references and self-study.
Download or read book Computer Vision ECCV 2012 written by Andrew Fitzgibbon and published by Springer. This book was released on 2012-09-26 with total page 913 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.
Download or read book Computer Assisted and Robotic Endoscopy written by Xiongbiao Luo and published by Springer. This book was released on 2014-11-22 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First International Workshop on Computer Assisted and Robotic Endoscopy, CARE 2014, held in conjunction with MICCAI 2014, in Boston, MA, USA, in September 2014. The 12 papers presented focus on recent technical advances associated with computer vision; graphics; robotics and medical imaging; external tracking systems; medical device control systems; information processing techniques; endoscopy; planning and simulation.
Download or read book Optical Flow Estimation in the Presence of Fast Or Discontinuous Motion written by Yan Niu and published by . This book was released on 2010 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the computation of optical flow, i.e., the motion perceived from a sequence of gradually changing images, as an estimate for the 2D velocity of the scene. Due to the large variety and high complexity of the motion types existing in practice, motion recovery requires the estimation process to be highly adaptive. This thesis investigates how to select and combine the reasoning rules, namely the optical flow constraints, according to the type of motion information detected. Moreover, the thesis extends optical flow computation to fast rotation, an important, frequent and challenging motion type, which has not been addressed much in the literature. The thesis starts by proposing various measures, based on theory as well as heuristics, for motion inconsistency detection. This facilitates selecting only the optical flow constraints that are valid for each pixel. While this selection benefits pixels affected by inconsistent motion, the combination of different constraints also enhances flow recovery for pixels that have consistent motion. Two frameworks are designed for the combination of flow constraints. One utilizes motion segmentation; and the other is close in spirit to Expectation-Maximization. Within these frameworks, new constraints are formulated and tested. Furthermore, the adaptive reasoning is generalized from translational motion to motion that includes fast rotation. The key concept that enables this generalization is the use of intrinsic directions in differential geometry. Experimental results on a variety of benchmark sequences have demonstrated the ability of the proposed methods to improve the performance of existing techniques in several situations, including strong motion discontinuities and fast rotational motion.
