A new frame interpolation method with pixel-level motion vector field

2014 ◽  
Author(s):  
Chuanxin Tang ◽  
Ronggang Wang ◽  
Wenmin Wang ◽  
Wen Gao
Keyword(s):  
Vector Field ◽  
Interpolation Method ◽  
Motion Vector ◽  
Frame Interpolation ◽  
Motion Vector Field

scholarly journals Frame interpolation with pixel-level motion vector field and mesh based hole filling

2016 ◽  
Vol 1 (1) ◽  
pp. 72-78 ◽  
Author(s):  
Chuanxin Tang ◽  
Ronggang Wang ◽  
Zhu Li ◽  
Wenmin Wang ◽  
Wen Gao
Keyword(s):  
Vector Field ◽  
Motion Vector ◽  
Hole Filling ◽  
Frame Interpolation ◽  
Motion Vector Field

scholarly journals Motion-Compensated Frame Interpolation Using Cellular Automata-Based Motion Vector Smoothing

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Ran Li ◽  
Ying Yin ◽  
Fengyuan Sun ◽  
Yanling Li ◽  
Lei You
Keyword(s):  
Cellular Automata ◽  
Motion Vector ◽  
Video Sequences ◽  
Frame Interpolation ◽  
Temporal Domain ◽  
Video Frames ◽  
Motion Compensated Frame Interpolation ◽  
Motion Vector Field ◽  
The Common ◽  
Temporal Symmetry

Motion-Compensated Frame Interpolation (MCFI) is one of the common temporal-domain tamper operations, and it is used to produce faked video frames for improving the visual qualities of video sequences. The instability of temporal symmetry results in many incorrect Motion Vectors (MVs) for Bidirectional Motion Estimation (BME) in MCFI. The existing Motion Vector Smoothing (MVS) works often oversmooth or revise correct MVs as wrong ones. To overcome this problem, we propose a Cellular Automata-based MVS (CA-MVS) algorithm to smooth the Motion Vector Field (MVF) output by BME. In our work, a cellular automaton is constructed to deduce MV outliers according to a defined local evolution rule. By performing CA-based evolution in a loop iteration, we gradually expose MV outliers and reduce incorrect MVs resulting from oversmoothing as many as possible. Experimental results show the proposed algorithm can improve the accuracy of BME and provide better objective and subjective interpolation qualities when compared with the traditional MVS algorithms.

scholarly journals Motion Vector Field Estimation Using Brightness Constancy Assumption and Epipolar Geometry Constraint

2014 ◽  
Vol II-1 ◽  
pp. 9-16 ◽  
Author(s):  
S. Hosseinyalamdary ◽  
A. Yilmaz
Keyword(s):  
Vector Field ◽  
Optical Flow ◽  
Motion Vector ◽  
Epipolar Geometry ◽  
Estimation Methods ◽  
Brightness Constancy ◽  
Flow Estimation ◽  
Optical Flow Estimation ◽  
Motion Vector Field ◽  
Field Estimation

In most Photogrammetry and computer vision tasks, finding the corresponding points among images is required. Among many, the Lucas-Kanade optical flow estimation has been employed for tracking interest points as well as motion vector field estimation. This paper uses the IMU measurements to reconstruct the epipolar geometry and it integrates the epipolar geometry constraint with the brightness constancy assumption in the Lucas-Kanade method. The proposed method has been tested using the KITTI dataset. The results show the improvement in motion vector field estimation in comparison to the Lucas-Kanade optical flow estimation. The same approach has been used in the KLT tracker and it has been shown that using epipolar geometry constraint can improve the KLT tracker. It is recommended that the epipolar geometry constraint is used in advanced variational optical flow estimation methods.

On avoiding singularities in redundant robot kinematics

Robotica ◽  
1995 ◽  
Vol 13 (6) ◽  
pp. 599-606 ◽  
Author(s):  
Krzysztof Tchoń ◽  
Aleksander Matuszok
Keyword(s):  
Vector Field ◽  
Equilibrium Points ◽  
Motion Vector ◽  
Sufficient Conditions ◽  
The Self ◽  
Robot Kinematics ◽  
Redundant Robot ◽  
Singular Configurations ◽  
Motion Vector Field ◽  
Self Motion

SummaryFor redundant robot kinematics with a degree of redundancy 1 a self-motion vector field is examined whose equilibrium points lie at singular configurations of the kinematics, and whose orbits determine the self-motion manifolds. It is proved that the self-motion vector field is divergence-free. Locally, around singular configurations of corank 1, the self-motion vector field defines a 2-dimensional Hamiltonian dynamical system. An analysis of the phase portrait of this system in a neighbourhood of a singular configuration solves completely the question of avoidability or unavoidability of this configuration. Complementarily, sufficient conditions for avoidability and unavoidability are proposed in an analytic form involving the self-motion Hamilton function. The approach is illustrated with examples. A connection with normal forms of kinematics is established.

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