IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
ECCV '90 Proceedings of the First European Conference on Computer Vision
Symmetrical Dense Optical Flow Estimation with Occlusions Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
Learning for Optical Flow Using Stochastic Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
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One of the key problems in computer vision is the estimation of motion in image sequences. The apparent displacement of the pixels through the image sequence is generally called optical flow. This is a low-level task that is the base for many other high-level applications, such us stereoscopic vision and 3D scene reconstruction, object tracking, ambient intelligence, video surveillance, medical image analysis, meteorological prediction and analysis, and so on. After many years of intense research, we may consider that the optical flow research field is not mature yet. The quality and amount of recent publications, with many important contributions, reflect that this is a very active field. It is attracting many researchers in computer vision that make evolve the field in a steady way. In this paper we examine the last contributions and most important ideas about optical flow that have appeared during the last years.