共查询到10条相似文献,搜索用时 156 毫秒
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Ravi Garg Anastasios Roussos Lourdes Agapito 《International Journal of Computer Vision》2013,104(3):286-314
This paper addresses the problem of non-rigid video registration, or the computation of optical flow from a reference frame to each of the subsequent images in a sequence, when the camera views deformable objects. We exploit the high correlation between 2D trajectories of different points on the same non-rigid surface by assuming that the displacement of any point throughout the sequence can be expressed in a compact way as a linear combination of a low-rank motion basis. This subspace constraint effectively acts as a trajectory regularization term leading to temporally consistent optical flow. We formulate it as a robust soft constraint within a variational framework by penalizing flow fields that lie outside the low-rank manifold. The resulting energy functional can be decoupled into the optimization of the brightness constancy and spatial regularization terms, leading to an efficient optimization scheme. Additionally, we propose a novel optimization scheme for the case of vector valued images, based on the dualization of the data term. This allows us to extend our approach to deal with colour images which results in significant improvements on the registration results. Finally, we provide a new benchmark dataset, based on motion capture data of a flag waving in the wind, with dense ground truth optical flow for evaluation of multi-frame optical flow algorithms for non-rigid surfaces. Our experiments show that our proposed approach outperforms state of the art optical flow and dense non-rigid registration algorithms. 相似文献
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Chin-Hung Teng Shang-Hong Lai Yung-Sheng Chen Wen-Hsing Hsu 《Computer Vision and Image Understanding》2005,97(3):315-346
In this paper, we present a very accurate algorithm for computing optical flow with non-uniform brightness variations. The proposed algorithm is based on a generalized dynamic image model (GDIM) in conjunction with a regularization framework to cope with the problem of non-uniform brightness variations. To alleviate flow constraint errors due to image aliasing and noise, we employ a reweighted least-squares method to suppress unreliable flow constraints, thus leading to robust estimation of optical flow. In addition, a dynamic smoothness adjustment scheme is proposed to efficiently suppress the smoothness constraint in the vicinity of the motion and brightness variation discontinuities, thereby preserving motion boundaries. We also employ a constraint refinement scheme, which aims at reducing the approximation errors in the first-order differential flow equation, to refine the optical flow estimation especially for large image motions. To efficiently minimize the resulting energy function for optical flow computation, we utilize an incomplete Cholesky preconditioned conjugate gradient algorithm to solve the large linear system. Experimental results on some synthetic and real image sequences show that the proposed algorithm compares favorably to most existing techniques reported in literature in terms of accuracy in optical flow computation with 100% density. 相似文献
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Andrés Bruhn Joachim Weickert Christoph Schnörr 《International Journal of Computer Vision》2005,61(3):211-231
Differential methods belong to the most widely used techniques for optic flow computation in image sequences. They can be classified into local methods such as the Lucas–Kanade technique or Bigün's structure tensor method, and into global methods such as the Horn/Schunck approach and its extensions. Often local methods are more robust under noise, while global techniques yield dense flow fields. The goal of this paper is to contribute to a better understanding and the design of novel differential methods in four ways; (i) We juxtapose the role of smoothing/regularisation processes that are required in local and global differential methods for optic flow computation. (ii) This discussion motivates us to describe and evaluate a novel method that combines important advantages of local and global approaches: It yields dense flow fields that are robust against noise. (iii) Spatiotemporal and nonlinear extensions as well as multiresolution frameworks are presented for this hybrid method. (iv) We propose a simple confidence measure for optic flow methods that minimise energy functionals. It allows to sparsify a dense flow field gradually, depending on the reliability required for the resulting flow. Comparisons with experiments from the literature demonstrate the favourable performance of the proposed methods and the confidence measure. 相似文献
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A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods 总被引:1,自引:0,他引:1
Andrés Bruhn Joachim Weickert Timo Kohlberger Christoph Schnörr 《International Journal of Computer Vision》2006,70(3):257-277
Variational methods are among the most accurate techniques for estimating the optic flow. They yield dense flow fields and
can be designed such that they preserve discontinuities, estimate large displacements correctly and perform well under noise
and varying illumination. However, such adaptations render the minimisation of the underlying energy functional very expensive
in terms of computational costs: Typically one or more large linear or nonlinear equation systems have to be solved in order
to obtain the desired solution. Consequently, variational methods are considered to be too slow for real-time performance.
In our paper we address this problem in two ways: (i) We present a numerical framework based on bidirectional multigrid methods
for accelerating a broad class of variational optic flow methods with different constancy and smoothness assumptions. Thereby,
our work focuses particularly on regularisation strategies that preserve discontinuities. (ii) We show by the examples of
five classical and two recent variational techniques that real-time performance is possible in all cases—even for very complex
optic flow models that offer high accuracy. Experiments show that frame rates up to 63 dense flow fields per second for image
sequences of size 160 × 120 can be achieved on a standard PC. Compared to classical iterative methods this constitutes a speedup
of two to four orders of magnitude. 相似文献
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The optical flow problem is reduced to an optimal control problem governed by a linear parabolic equation having the unknown velocity field (the optical flow) as drift term. This model is derived from a new assumption, that is, the brightness intensity is conserved on a moving pattern driven by a Gaussian stochastic process. The optimality conditions are deduced by a passage to the limit technique in an approximating optimal control problem introduced for a regularization purpose. Finally, the controller uniqueness is addressed. 相似文献
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3D Curves Reconstruction Based on Deformable Models 总被引:2,自引:0,他引:2
We present a new method, based on curve evolution, for the reconstruction of a 3D curve from two different projections. It is based on the minimization of an energy functional. Following the work on geodesic active contours by Caselles et al. (in Int. Conf. on Pattern Recognition, 1996, Vol. 43, pp. 693–737), we then transform the problem of minimizing the functional into a problem of geodesic computation in a Riemann space. The Euler-Lagrange equation of this new functional is derived and its associated PDE is solved using the level set formulation, giving the existence and uniqueness results. We apply the model to the reconstruction of a vessel from a biplane angiography. 相似文献
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Strong stability preserving (SSP) high order Runge–Kutta time discretizations were developed for use with semi-discrete method of lines approximations of hyperbolic partial differential equations, and have proven useful in many other applications. These high order time discretization methods preserve the strong stability properties of first order explicit Euler time stepping. In this paper we analyze the SSP properties of Runge Kutta methods for the ordinary differential equation u
t
=Lu where L is a linear operator. We present optimal SSP Runge–Kutta methods as well as a bound on the optimal timestep restriction. Furthermore, we extend the class of SSP Runge–Kutta methods for linear operators to include the case of time dependent boundary conditions, or a time dependent forcing term. 相似文献
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This work aims at observing the effect of the mortar element method applied to a geometry requiring refinement in the vicinity of singularities induced by the presence of sharp corners. We solve the two-dimensional incompressible Navier–Stokes equations with a spectral element method. Mortar elements allow for local polynomial refinement, since they allow for functional nonconformity. The problem solved is the flow in a channel partially obstructed by an obstacle representing a rectangular blade. 相似文献