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Joint coarse-and-fine reasoning for deep optical flow [PDF]
, 2017 © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
López, Antonio Manuel +4 more
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Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Full-motion cost volumes play a central role in current state-of-the-art optical flow methods. However, constructed using simple feature correlations, they lack the ability to encapsulate prior, or even non-local knowledge. This creates artifacts in poorly constrained ambiguous regions, such as occluded and textureless areas.
Zhang, F +3 more
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Low-Latency and Scene-Robust Optical Flow Stream and Angular Velocity Estimation
IEEE Access, 2021 Event cameras are bio-inspired sensors that capture intensity changes of pixels individually, and generate asynchronous and independent “events”.
Sangil Lee, H. Jin Kim
doaj +1 more source
Optical Flow Estimation versus Motion Estimation [PDF]
, 2012 Optical flow estimation is often understood to be identical to dense image based motion estimation. However, only under certain assumptions does optical flow coincide with the projection of the actual 3D motion to the image plane.
Baker, Simon +8 more
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Decomposition of Optical Flow on the Sphere [PDF]
, 2014 We propose a number of variational regularisation methods for the estimation and decomposition of motion fields on the $2$-sphere. While motion estimation is based on the optical flow equation, the presented decomposition models are motivated by recent ...
Kirisits, Clemens +2 more
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Direct Optical-Flow-Aware Computational Framework for 3D Reconstruction
IEEE Access, 2019 In this paper, a direct computational method is presented which combines optical flow and structure from motion (SfM) by putting the SfM problem in the framework of optical flow estimation. In other word, the optical flow is reparametrized in term of the
Huijuan Hu, Pei Chen
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INTUITIVE ESTIMATION OF SPEED USING MOTION AND MONOCULAR DEPTH INFORMATION
Studia Universitatis Babes-Bolyai: Series Informatica, 2020 Advances in deep learning make monocular vision approaches attractive for the autonomous driving domain. This work investigates a method for estimating the speed of the ego-vehicle using state-of-the-art deep neural network based optical flow and single-
Róbert Adrian RILL
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Optical Flow Estimation Based on Curvelet Transform and Spatio-temporal Derivatives [PDF]
Engineering and Technology Journal, 2010 Optical flow estimation is still one of the key problems in computer vision.When estimating the displacement field between two images, it is applied as soonas correspondences between pixels are needed.
Atheer A. Sabri
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Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators
, 2018 Robust velocity and position estimation is crucial for autonomous robot navigation. The optical flow based methods for autonomous navigation have been receiving increasing attentions in tandem with the development of micro unmanned aerial vehicles.
Ji, Tete +3 more
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ProbFlow: Joint Optical Flow and Uncertainty Estimation [PDF]
2017 IEEE International Conference on Computer Vision (ICCV), 2017 Optical flow estimation remains challenging due to untextured areas, motion boundaries, occlusions, and more. Thus, the estimated flow is not equally reliable across the image. To that end, post-hoc confidence measures have been introduced to assess the per-pixel reliability of the flow.
Anne S. Wannenwetsch +2 more
openaire +4 more sources