I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV, pages 141--150, Cambridge, April 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....The next four sections present the details of the steps. Section 8 shows results of the method on motion sequences, and Section 9 presents conclusions. 2 Our Approach Figure 1 illustrates the steps of our method. The input is a field of velocity vectors, derived via correlation or other means[11]. We then generate a dense tensor velocity field, which encodes not only velocity, but also estimates of confidence (saliency) and uncertainty. We then extract discontinuities from this field, which are found as locations of maximal velocity uncertainty using the tensor voting formalism. ....

I. Cohen and I. Herlin, "Optical flow and phase portrait methods for environmental satellite image sequences ", ECCV, Cambridge, April 1996, pp. 141150.

....a new div curl type smoothness term. Our method is validated on synthetic and real meteorological images. 1 INTRODUCTION The analysis of image sequences showing evolving fluid phenomena has numerous applications in domains such as environmental sciences (meteorology, climatology, oceanography [2]) medical imaging [9] or experimental fluid mechanics [4] Such analysis which might provide concerned expert with a great deal of valuable informations, requires as a prerequisite to have a good estimation of the instantaneous 2D apparent velocity field (commonly known as optical flow) of the ....

Cohen I and Herlin I. Optical flow and phase portrait methods for environmental satellite image sequences. Proc ECCV'96, pp II:141--150, Cambridge, UK, April 1996.

....image sequences. 1 Background: Fluid Motion Estimation In a number of domains, image sequences that involve fluid phenomena, have to be analyzed: In environmental sciences (oceanography, meteorology, climatology, etc. ocean and atmosphere evolutions are observed via satellite sensors [5, 9]; In medical imaging, blood flow can be monitored by angiography [14] In the field of fluid mechanics, aero and hydro dynamics experiments now routinely produce lots of video data [7, 10, 15] In all these domains of applications, camera offers in a versatile and non intrusive way, huge amounts ....

....this context. The design of alternate approaches dedicated to fluid motion thus constitutes a widely open domain of research. Our work is a contribution in this direction. As in standard motion analysis, two types of motion information can be sought. First, dense velocity (or displacement) fields [5, 9] constitute precious sources of information which can serve either as validation basis, or as input data for numerical models (e.g. in short term weather prediction) They are also used for visualization purposes, and allow to compute other quantities of interest, such as the vorticity of the ....

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I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV'96, pages II:141--150, Cambridge, UK, Apr. 1996.

....descent minimization algorithms. However, when it comes to designing accurate and robust methods, able for instance to handle and precisely locate discontinuities, more suitable energies are non quadratic with numerous local minima. The optical flow estimation is not an exception to this rule [4, 7, 13, 15]. Even within an incremental multiresolution formulation of the problem which is commonly thought as yielding a smooth version of the original problem one still has to face to difficult sequence of optimization problems. To cope efficiently with such global energy minimizations, we propose ....

....of dense optic flow estimation, the multigrid framework provides efficient motion estimators allowing to combine different parameterizations of the velocity field through an adaptive partition of the image grid. A compromise solution between local dense methods involving smoothness constraints [4, 7, 13, 15] and global parametric approaches assuming low order polynomial representation of the velocity field [1, 3, 5] is thus introduced. The resulting approach takes benefit both from the robustness and the richness of global parametric flow descriptions and from the flexibility of the local smoothness ....

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I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV'96, pages 141--150, April 1996.

.... in general) within Markovian framework, binary edge variables similar to Geman and Geman s line processes [19] have thus been introduced (see for instance [22] 28] 41] within anisotropic diffusion framework, non linear Euler Lagrange PDEs have been devised along the same philosophy [11] [14], 15] 32] 35] Adopting a more global viewpoint, Black has pointed out in [3] that the different problems we have just evoked can all be seen as deviations from a model (either the data model or the smoothing prior model) Though different in nature, they can hopefully be located and ....

I. Cohen and I. Herlin, Optical flow and phase portrait methods for environmental satellite image sequences, In Proc. Europ. Conf. Computer Vision, pages 141--150, Cambridge, UK, April 1996.

....descent minimization algorithms. However, when it comes to design accurate and robust methods, able to handle and to locate as precisely as possible discontinuities, energies tend to be non linear with numerous local minima. The optical flow estimation is not an exception to this rule [5, 9, 10, 19, 21, 25]. Even within an incremental multiresolution formulation of the problem (which is almost inescapable in case of long range motions to be estimated) one has to deal with a sequence of global optimization problems which remain tricky. To cope efficiently with such global energy minimization, we ....

....error between frame (t) and the frame (t 1) backward registered exceeds a certain threshold. However this approach does not make use of regularization. A different approach based on finite elements method considers a threshold on the normal flow field (which are directly accessible from the ofc) [9]. In this case the computation of the adaptative grid is done a priori. Our robust incremental motion model permits to directly have access to such information through the data auxiliary variables 4 and to use it on line. We consider an adaptative grid structure 4 More precisely, they account ....

I. COHEN and I. HERLIN. Optical flow and phase portrait methods for environmental satellite image sequences. In B. BUXTON and R. CIPOLLA, editors, Proc. Europ. Conf. Computer Vision, number 1064 in LNCS-Series, pages 141--150. Springer-Verlag, April 1996.

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I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV, pages 141--150, Cambridge, April 1996.

No context found.

I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV, pages 141--150, Cambridge, April 1996.

....the flow pattern classification RR n 2819 34 Isaac COHEN, Isabelle HERLIN Figure 12: A frame of the infrared image sequence. described in section 6.3 gives an accurate localization of the vortex. This processing was also applied to a SST image sequence in order to characterize ocean vortices [6]. The location of the detected vortex may further be used for a complete modeling of the vortex. Indeed, Herlin et al. [11] use a geometric modeling of the vortex structure based on the location of vortex rolls. This approach is very stable and is used for tracking vortex shape in an image ....

I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In Proceedings of the Fourth European Conference on Computer Vision 1996, Cambridge, April 1996. INRIA Non Uniform Multiresolution Method for Optical Flow and Phase Portrait Models: Environmental Applications37

....estimation approach based on feature points only. The detection of moving objects in the warped image sequence is performed by computing the residual motion. This can be achieved by using temporal gradients [4] and optical CVPR 98 Workshop on Interpretation of Visual Motion 2 flow techniques [2, 9]. A temporal integration of the variations can also be used, as proposed by [3] where the temporal derivatives of the image sequence are accumulated in order to locate regions where motion occurs. Our approach is based on the optical flow normal component, which takes into account the mapping ....

....we have cancelled the motion field induced by the displacement of the observer. The detection of moving objects is accomplished by computing the residual motion in this stabilized image sequence. This motion can be derived through different schemes such as temporal gradients [4] or optical flow [9, 2]. These detected variations are due to 3D structures, not properly handled by the affine model, or the moving objects in the scene. These regions are usually small and cannot be used to infer the 3D geometry of the moving object. However, we can use the redundancy of the information and its ....

I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV, pages 141--150, Cambridge, April 1996.

....the moving platform. We can therefore cancel the motion field induced by the displacement of the observer prior to detecting the moving objects in the scene using temporal gradients [Halevi and Weinshall, 1997] accumulated gradients [Davis and Bobick, 1997] or optical flow [Irani et al. 1992; Cohen and Herlin, 1996] techniques. Image variations are characterized through the normal component of the optical flow field. Normal flow is derived from image spatio temporal gradients using the geometric transform mapping the original frame to the selected reference frame or to the previous one. Let T ij denotes the ....

I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In ECCV, pages 141--150, Cambridge, April 1996.

....phenomena and infer some physical measurements used in atmospheric models. For example, meteorologist use clouds in meteosat images as landmarks for estimating their motion and characterize some subtropical phenomena. Several approaches can be used to track these phenomena: optical flow methods [4] or a method based on pointwise tracking of moving structures like vortices and fronts [1] In this paper, we develop a new method for pointwise tracking of structures by matching their contours. Hence, the deformation between two temporal occurrences will be obtained through a set of trajectories ....

I. Cohen and I. Herlin. Optical flow and phase portrait methods for environmental satellite image sequences. In Proceedings of the Fourth European Conference on Computer Vision 1996, Cambridge, April 1996.

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I. Cohen and I. Herlin, "Optical Flow and Phase Portrait Methods for Environmental Satellite Image Sequences", Proc. European Conf. Computer Vision, 1996, pp. 141-150.

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