Modern Numerical Weather Prediction (NWP) models produce forecasts which are effectively 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 relatively successful technique for modeling how images change temporally is called optical flow, wher...

Abstract In this paper, we address the problem of fluid motion estimation in image sequences. For such motions, standard optical flow methods, based on intensity conservation and spatial coherence of motion field, are not suitable. This is due to the highly deformable nature of fluid medium. For all applications where fluid motions are to be recovered from images, it is then important to have s...

In this paper, we present an observation model based on the Lucas and Kanade algorithm for computing optical flow, to track objects using particle filter algorithms. Although optical flow information enables us to know the displacement of objects present in a scene, it cannot be used directly to displace an object model since flow calculation techniques lack the necessary precision. In view of ...

We show how optical flow estimates can be combined with boundary estimation to improve estimates of motion. The improvement is associated with blending of estimates from complementary bases of operation. The paper combines a phase-based method for optical flow with a time extended version of the phase congruency operator. By evaluation on synthetic and real image sequences, the combination of t...

| Optical ow estimators of motion in image sequences are sometimes found using varia-tional frameworks, which produce partial diierential equations as the estimators. In this paper, we show that certain state-space formulations, solved by linear smoothing theory, lead to these same solutions. The advantages of viewing these problems in this way include explicit stochastic motion models, a prior...

As new technologies continue to develop, more and more robots are replacing humans in situations deemed too dangerous. However, current solutions are not fully automated, requiring offsite human operators for executing basic actions. The ideal solution would be a fully autonomous vehicle that could complete its objectives without any human intervention. In this project, the viability of optical...

In this work, we describe an implementation of the variational method proposed by Brox et al. in 2004, which yields accurate optical flows with low running times. It has several benefits with respect to the method of Horn and Schunck: it is more robust to the presence of outliers, produces piecewise-smooth flow fields and can cope with constant brightness changes. This method relies on the brig...

This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired as the background behind the refracting object moves. By structure here we mean a representation of how the object warps and attenuates (or amplifies) the light passing through it. We dist...

This paper proposes a new approach to image-based rendering that generates an image viewed from an arbitrary camera position and orientation by rendering optical flows extracted from reference images. To derive valid optical flows, we develop an analysis technique that improves the quality of stereo matching. Without using any special equipments such as range cameras, this technique constructs ...

The original optical flow algorithm [1] dealt with a flow field that could vary from place to place in the image, as would typically occur when a camera is moved through a three-dimensional environment—or if objects moved in front of a fixed camera. A related, but simpler problem, is that of recovering the motion of an image, all parts of which move with the same velocity (section 4.3 in [2]). ...