Results 231 to 240 of about 3,878,820 (309)

BMBC: Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolation

European Conference on Computer Vision, 2020
Video interpolation increases the temporal resolution of a video sequence by synthesizing intermediate frames between two consecutive frames. We propose a novel deep-learning-based video interpolation algorithm based on bilateral motion estimation. First,
Jun-ho Park, Keunsoo Ko, Chulwoo Lee, Chang-Su Kim   +3 more
semanticscholar   +1 more source

3D Human Motion Estimation via Motion Compression and Refinement

Asian Conference on Computer Vision, 2020
We develop a technique for generating smooth and accurate 3D human pose and motion estimates from RGB video sequences. Our method, which we call Motion Estimation via Variational Autoencoder (MEVA), decomposes a temporal sequence of human motion into a ...
Zhengyi Luo, S. Golestaneh, Kris M. Kitani   +2 more
semanticscholar   +1 more source

Estimation of an affine motion

2009 American Control Conference, 2009
This paper discusses the 3D affine motion estimation problem using two cameras via observations of a single feature point. The unknown parameters to be estimated include the nine rotational parameters, the three translational parameters, and the 3D position. One camera assumes a parabolic projection. The other camera is the conventional camera that has
Lili Ma, Chengyu Cao, Naira Hovakimyan, Craig A. Woolsey, Guoqiang Hu 0001   +4 more
openaire   +1 more source

Unsupervised-Learning-Based Continuous Depth and Motion Estimation With Monocular Endoscopy for Virtual Reality Minimally Invasive Surgery

IEEE Transactions on Industrial Informatics, 2020
Three-dimensional display and virtual reality technology have been applied in minimally invasive surgery to provide doctors with a more immersive surgical experience. One of the most popular systems based on this technology is the Da Vinci surgical robot
Ling Li, Xiaojian Li, Shanlin Yang, Shuai Ding, A. Jolfaei, Xi Zheng   +5 more
semanticscholar   +1 more source

Motion segmentation and estimation

Proceedings of 1st International Conference on Image Processing, 2002
Applies mean field technique and presents a deterministic algorithm to determine the optical flow and motion boundaries. To deal with the problem of large motion, the authors present an adaptive multigrid approach, which also greatly reduces the computation time. This algorithm is fully parallelizable and iterative.
Tian, Tina Yu, Shah, M.
openaire   +2 more sources

Randomized motion estimation

2010 IEEE International Conference on Image Processing, 2010
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast motion relative to the magnitude of the image gradient. In this paper, we propose a fast random search algorithm to estimate motion.
Sylvain Boltz, Frank Nielsen
openaire   +1 more source

Motion Pyramid Networks for Accurate and Efficient Cardiac Motion Estimation

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020
Cardiac motion estimation plays a key role in MRI cardiac feature tracking and function assessment such as myocardium strain. In this paper, we propose Motion Pyramid Networks, a novel deep learning-based approach for accurate and efficient cardiac ...
Hanchao Yu, Xiao Chen, Humphrey Shi, Terrence Chen, Thomas S. Huang, Shanhui Sun   +5 more
semanticscholar   +1 more source

Motion estimation optimization

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992
Motion estimation is cast as a problem in energy minimization. This is achieved by modeling the displacement field as a Markov random field. The equivalence of a Markov random field and a Gibbs distribution is then used to convert the problem into one of defining an appropriate energy function that describes the motion and any constraints imposed on it.
Sarah A. Rajala, Ikhlas M. Abdelqader, Griff L. Bilbro, Wesley E. Snyder   +3 more
openaire   +1 more source

Segmentation and motion estimation

1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002
We present an algorithm that combines image segmentation and motion field estimation. The segmentation includes the occluded and uncovered background regions, the self-occluded and uncovered object regions, and the common moving regions of the objects.
Hamid Naseri, John A. Stuller
openaire   +1 more source

Motion estimation and segmentation

Machine Vision and Applications, 1996
In the general structure-from-motion (SFM) problem involving several moving objects in a scene, the essential first step is to segment moving objects independently. We attempt to deal with the problem of optical flow estimation and motion segmentation over a pair of images. We apply a mean field technique to determine optical flow and motion boundaries
Tina Yu Tian, Mubarak Shah
openaire   +3 more sources