Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
Optical flow can be reliably estimated between areas visible in two images, but not in occlusion areas. If optical flow is needed in the whole image domain, one approach is to use ...
Subspace based factorization methods are commonly used for a variety of applications, such as 3D reconstruction, multi-body segmentation and optical flow estimation. These are usu...
Digital Particle Image Velocimetry (DPIV) aims at flow visualisation and measurement of flow dynamics in numerous applications, including hydrodynamics, combustion processes and a...
Optical flow estimation from image sequences has been for several years a mathematical process carried out by general purpose processors in no real time. In this work a specific a...
Gradient-based optical flow estimation methods such as LucasKanade method work well for scenes with small displacements but fail when objects move with large displacements. Hierar...
Optical flow is widely in use in the field of image processing. In general, optical flow is computed from luminance images. However, optical flow based on luminance information hi...
We present a new reliable hybrid recursive method for optical flow estimation. The method efficiently combines the advantage of discrete motion estimation and optical flow estimati...
Using the variational approaches to estimate optical flow between two frames, the flow discontinuities between different motion fields are usually not distinguished even when an an...
Jiangjian Xiao, Hui Cheng, Harpreet S. Sawhney, Ce...
Abstract. We study an energy functional for computing optical flow that combines three assumptions: a brightness constancy assumption, a gradient constancy assumption, and a discon...