Authors:
Michael Santoro
;
Ghassan Al-Regib
and
Yucel Altunbasak
Affiliation:
Georgia Institute of Technology, United States
Keyword(s):
Block Matching, True Motion Estimation (ME), HBM: Smoothness Constraints, Regularization, Recursive Search (RS).
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image and Video Coding and Compression
;
Image Formation and Preprocessing
;
Image Registration
;
Motion, Tracking and Stereo Vision
;
Optical Flow and Motion Analyses
;
Pattern Recognition
;
Robotics
;
Software Engineering
;
Tracking and Visual Navigation
Abstract:
Since motion estimation via block matching is an ill-posed problem, it requires the use of smoothness constraints to regularize the motion field. The block matching error and smoothness constraints together form an energy expression to be minimized. Motion vectors (MVs) from a candidate set are used to determine which MV minimizes the overall energy. These MVs, which may consist of spatial or temporal MVs, determine the quality of the motion field. Therefore, to ensure a high-quality motion field, we propose a new method to
improve the quality of the MVs. The proposed method uses a novel approach to incorporate prior spatial MVs into block matching. By incorporating these MVs into block matching, we significantly reduce the size of the candidate set and improve the quality of the motion field.