Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
GIBBS RANDOM FIELD MODEL BASED 3-D MOTION ESTIMATION BY WEAKENED RIGIDITY
Date
1994-01-01
Author
Alatan, Abdullah Aydın
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
226
views
0
downloads
Cite This
3-D motion estimation from a video sequence remains a challenging problem. Modelling the local interactions between the 3-D motion parameters is possible by using Gibbs random fields. An energy function which gives the joint probability distribution of the motion vectors, is constructed. The most probable motion vector set is found by maximizing the probability, represented by this distribution. Since the 3-D motion estimation problem is ill-posed, the regularization is achieved by an initial rigidity assumption. Afterwards, the rigidity is weakened hierarchically, until the finest level is reached. At the finest level, each point has its own motion vector and the "weak-connection" between these vectors are described by the energy function. The high computational cost Q decreased considerably by the multiprecision approach. The simulation results support all our discussions.
Subject Keywords
Motion estimation
,
Cost function
,
Equations
,
Power engineering and energy
,
Video sequences
,
Probability distribution
,
Computational modeling
,
Layout
,
Image segmentation
,
Image restoration
URI
https://hdl.handle.net/11511/41003
DOI
https://doi.org/10.1109/icip.1994.413679
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
MULTI-RESOLUTION MOTION ESTIMATION FOR MOTION COMPENSATED FRAME INTERPOLATION
Guenyel, Bertan; Alatan, Abdullah Aydın (2010-09-29)
A multi-resolution motion estimation scheme is proposed for tracking of the true 2D motion in video sequences for motion compensated image interpolation. The proposed algorithm utilizes frames with different resolutions and adaptive block dimensions for efficient representation of motion. Firstly, motion vectors for each block are assigned as a result of predictive search in each pass. Then, the outlier motion vectors are detected and corrected at the end of each pass. Simulation results with respect to dif...
Object Segmentation in Multi-view Video via Color, Depth and Motion Cues
Cigla, Cevahir; Alatan, Abdullah Aydın (2009-01-01)
In the light of dense depth map estimation, motion estimation and object segmentation, the research on multi-view video (MVV) content has becoming increasingly popular due to its wide application areas in the near future. In this work, object segmentation problem is studied by additional cues due to depth and motion fields. Segmentation is achieved by modeling images as graphical models and performing popular Normalized Cuts method with some modifications. In the graphical models, each node is represented b...
Prioritized sequential 3D reconstruction in video sequences with multiple motions
Imre, Evren; Knorr, Sebastian; Alatan, Abdullah Aydın; Sikora, Thomas (2006-10-11)
in this study, an algorithm is proposed to solve the multi-frame structure from motion (MFSfM) problem for monocular video sequences in dynamic scenes. The algorithm uses the epipolar criterion to segment the features belonging to independently moving objects. Once the features are segmented, corresponding objects are reconstructed individually by using a sequential algorithm, which is also capable of prioritizing the frame pairs with respect to their reliability and information content, thus achieving a fa...
3-D motion estimation of rigid objects for video coding applications using an improved iterative version of the E-matrix method
Alatan, Abdullah Aydın (1998-02-01)
As an alternative to current two-dimensional (2-D) motion models, a robust three-dimensional (3-D) motion estimation method is proposed to be utilized in object-based video coding applications, Since the popular E-matrix method is well known for its susceptibility to input errors, a performance indicator, which tests the validity of the estimated 3-D motion parameters both explicitly and implicitly, is defined. This indicator is utilized within the RANSAC method to obtain a robust set of 2-D motion correspo...
TEMPORALLY CONSISTENT LAYER DEPTH ORDERING VIA PIXEL VOTING FOR PSEUDO 3D REPRESENTATION
Turetken, Engin; Alatan, Abdullah Aydın (2009-05-06)
A new region-based depth ordering algorithm is proposed based on the segmented motion layers with affine motion models. Starting from an initial set of layers that are independently extracted for each frame of an input sequence, relative depth order of every layer is determined following a bottom-to-top approach from local pair-wise relations to a global ordering. Layer sets of consecutive time instants are warped in two opposite directions in time to capture pair-wise occlusion relations of neighboring lay...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. A. Alatan, “GIBBS RANDOM FIELD MODEL BASED 3-D MOTION ESTIMATION BY WEAKENED RIGIDITY,” 1994, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41003.