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A Segmentation Based Variational Model for Accurate Optical Flow Estimation
[chapter]
2008
Lecture Notes in Computer Science
Preserved Fulltext
First, we partition the input images and integrate the segmentation information into a variational model where each of the segments is constrained by an affine motion. ...
Extensive experiments show that the proposed method not only produces quantitatively accurate optical flow estimates but also preserves sharp motion boundaries, which makes the optical flow result usable ...
Acknowledgements We thank Guofeng Zhang for his comments on this paper. This work was fully supported by a grant from the Research Grants Council of Hong Kong (Project No. 412708). ...
doi:10.1007/978-3-540-88682-2_51
fatcat:3crwupvplzez5bzfpdq6n4ek7u
Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel
[article]
2017
arXiv
pre-print
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In this paper, we exploit semantic segmentation in each blurry frame to understand the scene contents and use different motion models for image regions to guide optical flow estimation. ...
Optical flow can be used for kernel estimation since it predicts motion trajectories. ...
Second, we exploit semantic segmentation to account for occlusions and blurry edges for accurate optical flow estimation. ...
arXiv:1708.03423v1
fatcat:ztfjqbiyajcubatwzihhvmbrxe
Video Deblurring via Semantic Segmentation and Pixel-Wise Non-linear Kernel
2017
2017 IEEE International Conference on Computer Vision (ICCV)
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In this paper, we exploit semantic segmentation in each blurry frame to understand the scene contents and use different motion models for image regions to guide optical flow estimation. ...
Optical flow can be used for kernel estimation since it predicts motion trajectories. ...
Second, we exploit semantic segmentation to account for occlusions and blurry edges for accurate optical flow estimation. ...
doi:10.1109/iccv.2017.123
dblp:conf/iccv/RenPC017
fatcat:cvz7fjcrwrfqzipu63tzxre5vm
Object Segmentation Tracking from Generic Video Cues
[article]
2020
arXiv
pre-print
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We propose a light-weight variational framework for online tracking of object segmentations in videos based on optical flow and image boundaries. ...
While high-end computer vision methods on this task rely on sequence specific training of dedicated CNN architectures, we show the potential of a variational model, based on generic video information from ...
All further results are based on this setting. 2) Flow Estimation Methods: Optical flow information is a central component of our model. ...
arXiv:1910.02258v3
fatcat:aw6wouvesbfgjgg2vihfqcnkja
Generalized Video Deblurring for Dynamic Scenes
[article]
2015
arXiv
pre-print
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Therefore, we propose a single energy model that simultaneously estimates optical flows and latent frames to solve our deblurring problem. ...
By minimizing the proposed energy function, we achieve significant improvements in removing blurs and estimating accurate optical flows in blurry frames. ...
By estimating a pixel-wise kernel using optical flows, we handled general blurs. Thus, we proposed a new energy model that estimates optical flows and latent frames, jointly. ...
arXiv:1507.02438v1
fatcat:rg3oicetsbgfhils76n5kioxx4
Generalized video deblurring for dynamic scenes
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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Therefore, we propose a single energy model that simultaneously estimates optical flows and latent frames to solve our deblurring problem. ...
By minimizing the proposed energy function, we achieve significant improvements in removing blurs and estimating accurate optical flows in blurry frames. ...
By estimating a pixel-wise kernel using optical flows, we handled general blurs. Thus, we proposed a new energy model that estimates optical flows and latent frames, jointly. ...
doi:10.1109/cvpr.2015.7299181
dblp:conf/cvpr/KimL15a
fatcat:itv3caqg7rbctclrfweogvkxcy
SS-SF: Piecewise 3D Scene Flow Estimation with Semantic Segmentation
2021
IEEE Access
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Second, we plan a novel energy function to optimize the initial mappings by using a semantic segmentation constraint term to regularize the classical scene flow model, which the optimized mappings are ...
In order to address the issue of edge-blurring and improve the accuracy and robustness of scene flow estimation under motion occlusions, we in this article propose a piecewise 3D scene flow estimation ...
For example, in order to gain a robust computation scheme, Gottfried et al. [39] investigated a variational framework for RGB-D scene flow estimation. ...
doi:10.1109/access.2021.3055939
fatcat:nhefqnwjmzh2vd3ncbbaajwzwa
Dense, accurate optical flow estimation with piecewise parametric model
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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This paper proposes a simple method for estimating dense and accurate optical flow field. It revitalizes an early idea of piecewise parametric flow model. ...
A key innovation is that, we fit a flow field piecewise to a variety of parametric models, where the domain of each piece (i.e., each piece's shape, position and size) is determined adaptively, while at ...
JY is a CSC-cofunded BIT-ANU joint PhD student. The authors would like to thank AC and anonymous reviewers for invaluable comments. ...
doi:10.1109/cvpr.2015.7298704
dblp:conf/cvpr/YangL15
fatcat:dqjskno26bhtjfb5vnszqnqhha
Variational Motion Segmentation with Level Sets
[chapter]
2006
Lecture Notes in Computer Science
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We suggest a variational method for the joint estimation of optic flow and the segmentation of the image into regions of similar motion. ...
It need not fear a quantitative comparison to pure optic flow estimation techniques: For the popular Yosemite sequence with clouds we obtain the currently most accurate result. ...
Acknowledgements We thank Luis Garrido (University Pompeu Fabral, Barcelona, Spain) for raising the question if there is an error in the ground truth of the Yosemite sequence. ...
doi:10.1007/11744023_37
fatcat:dw2cs3gcj5c7tlsfmvtuoaioam
A General Dense Image Matching Framework Combining Direct and Feature-Based Costs
2013
2013 IEEE International Conference on Computer Vision
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Dense motion field estimation (typically optical flow, stereo disparity and surface registration) is a key computer vision problem. ...
The feature-based cost is built around a novel robust distance function that handles keypoints and "weak" features such as segments. ...
Their method remains a reference in optical flow estimation for its robustness and accuracy, but we identified several limitations. ...
doi:10.1109/iccv.2013.30
dblp:conf/iccv/Braux-ZinDB13
fatcat:fmis34zujvg43bpmie4vt42vga
A Feature-Based Approach for Determining Dense Long Range Correspondences
[chapter]
2004
Lecture Notes in Computer Science
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For this reason, to achieve dense optical flow for image sequences with large inter-frame disparity, we propose a two stage process in which a planar model is used to get an approximation for the segmentation ...
Planar motion models can provide gross motion estimation and good segmentation for image pairs with large inter-frame disparity. ...
We would like to thank Sameer Agarwal, Charless Fowlkes and Ben Ochoa for helpful discussions. The images in Figures ...
doi:10.1007/978-3-540-24672-5_14
fatcat:crkdiz55afhvvnjg7jfjmzxl5y
Motion Estimation Using Region-Level Segmentation and Extended Kalman Filter for Autonomous Driving
2021
Remote Sensing
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We first use a region-level segmentation to accurately locate the object region for the latter two stages. ...
In the stage of parameter estimate, we develop a relative motion model of the ego-vehicle and the object, and accordingly establish an EKF model for point tracking and parameter estimate. ...
In this study, we leverage a region-level segmentation to accurately locate object regions for tracking and parameter estimate. ...
doi:10.3390/rs13091828
fatcat:pbxdishdtnh4tdo5uhxydw7rhi
Efficient Uncertainty Estimation for Semantic Segmentation in Videos
[article]
2018
arXiv
pre-print
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A deep learning model can't be applied in real applications if we don't know whether the model is certain about the decision or not. ...
For real-time applications such as a self-driving car system, which needs to obtain the prediction and the uncertainty as fast as possible, so that MC dropout becomes impractical. ...
For some regions that contain fast moving objects or occlusion, the optical flow may not be accurate. ...
arXiv:1807.11037v1
fatcat:trbnkqwcevdsnara2i2dszsyre
Dynamic Texture Detection Based on Motion Analysis
2008
International Journal of Computer Vision
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Motion estimation is usually based on the brightness constancy assumption. ...
Accurate segmentation into regions of static and dynamic texture is achieved using a level set scheme. ...
Acknowledgements This research was supported partly by MUS-CLE: Multimedia Understanding through Semantics, Computation and Learning, a European Network of Excellence funded by the EC 6th Framework IST ...
doi:10.1007/s11263-008-0184-y
fatcat:ankxf2eazfentlnmkxo26jkpfy
Real-time object tracking and segmentation using adaptive color snake model
2005
31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005.
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An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. ...
In this paper, the development of new snake model called "adaptive color snake model (ACSM)" for segmentation and tracking is introduced. The simple operation makes the algorithm runs in real-time. ...
As the camera moves, the system generates many variations between successive images. Optical flow-based approach is not suitable for these situations. ...
doi:10.1109/iecon.2005.1569195
fatcat:dg2c2jyvknft5c34m5kzufpcfm
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