D Zhang, G Lu - Circuits, Systems and Signal Processing, 2001 - Springer
Segmentation of objects in image sequences is very important in many aspects of multimedia applications. In second-generation image/video coding, images are segmented …
M Zhai, X Xiang, N Lv, X Kong - Pattern Recognition, 2021 - Elsevier
Motion analysis is one of the most fundamental and challenging problems in the field of computer vision, which can be widely applied in many areas, such as autonomous driving …
D Fortun, P Bouthemy, C Kervrann - Computer Vision and Image …, 2015 - Elsevier
Optical flow estimation is one of the oldest and still most active research domains in computer vision. In 35 years, many methodological concepts have been introduced and …
Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a …
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 …
Differential methods belong to the most widely used techniques for optic flow computation in image sequences. They can be classified into local methods such as the Lucas–Kanade …
In this paper, we make contact with the field of nonparametric statistics and present a development and generalization of tools and results for use in image processing and …
T Gautama, MA Van Hulle - IEEE transactions on neural …, 2002 - ieeexplore.ieee.org
We introduce a new technique for estimating the optical flow field, starting from image sequences. As suggested by Fleet and Jepson (1990), we track contours of constant phase …
J Weickert, C Schnörr - International Journal of Computer Vision, 2001 - Springer
Many differential methods for the recovery of the optic flow field from an image sequence can be expressed in terms of a variational problem where the optic flow minimizes some …