Results 261 to 270 of about 94,408 (300)
Some of the next articles are maybe not open access.
Biological Cybernetics, 1987
We employ an optimal solution to both the "shape from motion problem" and the related problem of the estimation of self-movement on a purely optical basis to deduce practical rules of thumb for the limits of the optic flow information content in the presence of perturbation of the motion parallax field. The results are illustrated and verified by means
Koenderink, J. J., van Doorn, Andrea J.
openaire +2 more sources
We employ an optimal solution to both the "shape from motion problem" and the related problem of the estimation of self-movement on a purely optical basis to deduce practical rules of thumb for the limits of the optic flow information content in the presence of perturbation of the motion parallax field. The results are illustrated and verified by means
Koenderink, J. J., van Doorn, Andrea J.
openaire +2 more sources
2006 3rd International Conference on Broadband Communications, Networks and Systems, 2006
In this work, we evaluate an attractive candidate for optical network data transport: optical flow switching (OFS). We describe the operation and implementation of the architecture, characterize its capacity region and capacity-cost tradeoff, and compare it to other prominent optical network architectures.
Vincent W. S. Chan +2 more
openaire +1 more source
In this work, we evaluate an attractive candidate for optical network data transport: optical flow switching (OFS). We describe the operation and implementation of the architecture, characterize its capacity region and capacity-cost tradeoff, and compare it to other prominent optical network architectures.
Vincent W. S. Chan +2 more
openaire +1 more source
2007
One of the main technique used to recover motion analysis from two images or to register them is variational optical flow, where the pixels of one image are matched to the pixels of the second image by minimizing an energy functional. In the standard formulation of variational optical flow, the estimated motion vector field depends on the reference ...
Luis Álvarez 0001 +6 more
openaire +2 more sources
One of the main technique used to recover motion analysis from two images or to register them is variational optical flow, where the pixels of one image are matched to the pixels of the second image by minimizing an energy functional. In the standard formulation of variational optical flow, the estimated motion vector field depends on the reference ...
Luis Álvarez 0001 +6 more
openaire +2 more sources
2012 Ninth Conference on Computer and Robot Vision, 2012
We implement and quantitatively/qualitatively evaluate two optical flow methods that model occlusion. The Yuan et al. method \cite{Yuan-et-al-2006} improves on the Horn and Schunck optical flow method at occlusion boundaries by using a dynamic coefficient (the Lagrange multiplier $\alpha$) at each pixel that weighs the smoothness constraint relative to
Jieyu Zhang, John L. Barron
openaire +1 more source
We implement and quantitatively/qualitatively evaluate two optical flow methods that model occlusion. The Yuan et al. method \cite{Yuan-et-al-2006} improves on the Horn and Schunck optical flow method at occlusion boundaries by using a dynamic coefficient (the Lagrange multiplier $\alpha$) at each pixel that weighs the smoothness constraint relative to
Jieyu Zhang, John L. Barron
openaire +1 more source
SIAM Journal on Control and Optimization, 2005
The author considers the optical flow equation \[ \frac{\partial }{\partial t}I+V\cdot\nabla I=0,\quad I(0)=I_0 \tag{1} \] in \([0,T]\times \Omega\), \(\Omega\in \mathbb{R}^d\), and given a target image \(I_1\) at \(T\) he finds \(V\) such that \(I(T)=I_1\).
openaire +2 more sources
The author considers the optical flow equation \[ \frac{\partial }{\partial t}I+V\cdot\nabla I=0,\quad I(0)=I_0 \tag{1} \] in \([0,T]\times \Omega\), \(\Omega\in \mathbb{R}^d\), and given a target image \(I_1\) at \(T\) he finds \(V\) such that \(I(T)=I_1\).
openaire +2 more sources
1990
The analysis of time-varying image sequences is a classical problem of machine vision (Aggarwal & Nandhakumar, 1988; Ullman, 1979), but is likely to be very useful in robotics, passive navigation and several other fields. Two major approaches have been proposed for the analysis of image sequences: one based on differential techniques aims at computing ...
De Micheli Enrico +3 more
openaire +2 more sources
The analysis of time-varying image sequences is a classical problem of machine vision (Aggarwal & Nandhakumar, 1988; Ullman, 1979), but is likely to be very useful in robotics, passive navigation and several other fields. Two major approaches have been proposed for the analysis of image sequences: one based on differential techniques aims at computing ...
De Micheli Enrico +3 more
openaire +2 more sources
Computer Graphics Forum, 1998
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.
Park, TJ +2 more
openaire +2 more sources
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.
Park, TJ +2 more
openaire +2 more sources
The computation of optical flow
ACM Computing Surveys, 1995Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements.
Steven S. Beauchemin, John L. Barron
openaire +1 more source
Robust Optical Flow Integration
IEEE Transactions on Image Processing, 2015We analyze the problem of how to correctly construct dense point trajectories from optical flow fields. First, we show that simple Euler integration is unavoidably inaccurate, no matter how good is the optical flow estimator. Then, an inverse integration scheme is analyzed which is more robust to bias and input noise and shows better stability ...
Tomás Crivelli +4 more
openaire +4 more sources
Optic Flow and Autonomous Navigation
Perception, 1995Many animals, especially insects, compute and use optic flow to control their motion direction and to avoid obstacles. Recent advances in computer vision have shown that an adequate optic flow can be computed from image sequences. Therefore studying whether artificial systems, such as robots, can use optic flow for similar purposes is of particular ...
CAMPANI M, GIACHETTI A, TORRE V
openaire +2 more sources