Results 1 - 10 of 1,992

A database and evaluation methodology for optical flow

by Simon Baker, Daniel Scharstein, J. P. Lewis, Stefan Roth, Michael J. Black, Richard Szeliski - In Proceedings of the IEEE International Conference on Computer Vision , 2007
"... The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex n ..."
Abstract - Cited by 407 (22 self) - Add to MetaCart
The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex

Determining Optical Flow

by Berthold K. P. Horn, Brian G. Schunck - ARTIFICIAL INTELLIGENCE , 1981
"... Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent veloc ..."
Abstract - Cited by 2404 (9 self) - Add to MetaCart
velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely

Hierarchical model-based motion estimation

by James R. Bergen, P. Anandan, Th J. Hanna, Rajesh Hingorani , 1992
"... This paper describes a hierarchical estimation framework for the computation of diverse representations of motion information. The key features of the resulting framework (or family of algorithms) a,re a global model that constrains the overall structure of the motion estimated, a local rnodel that ..."
Abstract - Cited by 664 (15 self) - Add to MetaCart
that is used in the estimation process, and a coa,rse-fine refinement strategy. Four specific motion models: affine flow, planar surface flow, rigid body motion, and general optical flow, are described along with their application to specific examples.

Efficient belief propagation for early vision

by Pedro F. Felzenszwalb, Daniel P. Huttenlocher - In CVPR , 2004
"... Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advances are often still too slow for practical u ..."
Abstract - Cited by 515 (8 self) - Add to MetaCart
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph cuts and belief propagation yield accurate results, but despite recent advances are often still too slow for practical

Lucas-Kanade 20 Years On: A Unifying Framework: Part 3

by Simon Baker, Ralph Gross, Iain Matthews - International Journal of Computer Vision , 2002
"... Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms hav ..."
Abstract - Cited by 706 (30 self) - Add to MetaCart
Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms

Sizing Router Buffers

by Guido Appenzeller, Isaac Keslassy, Nick McKeown , 2004
"... All Internet routers contain buffers to hold packets during times of congestion. Today, the size of the buffers is determined by the dynamics of TCP’s congestion control algorithm. In particular, the goal is to make sure that when a link is congested, it is busy 100 % of the time; which is equivalen ..."
Abstract - Cited by 352 (17 self) - Add to MetaCart
All Internet routers contain buffers to hold packets during times of congestion. Today, the size of the buffers is determined by the dynamics of TCP’s congestion control algorithm. In particular, the goal is to make sure that when a link is congested, it is busy 100 % of the time; which

Robust multiresolution estimation of parametric motion models

by J. M. Odobez, P. Bouthemy - Jal of Vis. Comm. and Image Representation , 1995
"... This paper describes a method to estimate parametric motion models. Motivations for the use of such models are on one hand their efficiency, which has been demonstrated in numerous contexts such as estimation, segmentation, tracking and interpretation of motion, and on the other hand, their low comp ..."
Abstract - Cited by 329 (55 self) - Add to MetaCart
computational cost compared to optical flow estimation. However, it is important to have the best accuracy for the estimated parameters, and to take into account the problem of multiple motion. We have therefore developed two robust estimators in a multiresolution framework. Numerical results support

Action Recognition by Dense Trajectories

by Heng Wang , Alexander Kläser , Cordelia Schmid , Liu Cheng-lin , 2011
"... Feature trajectories have shown to be efficient for rep-resenting videos. Typically, they are extracted using the KLT tracker or matching SIFT descriptors between frames. However, the quality as well as quantity of these trajecto-ries is often not sufficient. Inspired by the recent success of dense ..."
Abstract - Cited by 293 (16 self) - Add to MetaCart
sampling in image classification, we propose an approach to describe videos by dense trajectories. We sam-ple dense points from each frame and track them based on displacement information from a dense optical flow field. Given a state-of-the-art optical flow algorithm, our trajec-tories are robust to fast

Secrets of Optical Flow Estimation and Their Principles

by Deqing Sun, Stefan Roth, Michael J. Black , 2010
"... The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible throu ..."
Abstract - Cited by 195 (10 self) - Add to MetaCart
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible

A finite-volume, incompressible Navier–Stokes model for studies of the ocean on parallel computers.

by John Marshall , Alistair Adcroft , Chris Hill , Lev Perelman , Curt Heisey - J. Geophys. Res., , 1997
"... Abstract. The numerical implementation of an ocean model based on the incompressible Navier Stokes equations which is designed for studies of the ocean circulation on horizontal scales less than the depth of the ocean right up to global scale is described. A "pressure correction" method i ..."
Abstract - Cited by 293 (32 self) - Add to MetaCart
of the Poisson operator and so leads to a single algorithm that seamlessly moves from nonhydrostatic to hydrostatic limits. Thus in the hydrostatic limit the model is "fast," competitive with the fastest ocean climate models in use today based on the hydrostatic primitive equations
Results 1 - 10 of 1,992