Paper Info
Title
3D motion flow estimation using local all-pass filters
Abstract
Fast and accurate motion estimation is an important tool in biomedical imaging applications such as motion compensation and image registration. In this paper, we present a novel algorithm to estimate motion in volumetric images based on the recently developed Local All-Pass (LAP) optical flow framework. The framework is built upon the idea that any motion can be regarded as a local rigid displacement and is hence equivalent to all-pass filtering. Accordingly, our algorithm aims to relate two images, on a local level, using a 3D all-pass filter and then extract the local motion flow from the filter. As this process is based on filtering, it can be efficiently repeated over the whole image volume allowing fast estimation of a dense 3D motion. We demonstrate the effectiveness of this algorithm on both synthetic motion flows and in-vivo MRI data involving respiratory motion. In particular, the algorithm obtains greater accuracy for significantly reduced computation time when compared to competing approaches.
Year
DOI
Venue
2016
10.1109/ISBI.2016.7493264
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Keywords
Field
DocType
Motion Estimation,All-Pass Filters,Optical Flow,Approximation,MR Images
Structure from motion,Computer vision,Quarter-pixel motion,Motion field,Computer science,Motion compensation,Filter (signal processing),Artificial intelligence,Motion estimation,Optical flow,Image registration
Conference
ISSN
Citations 
PageRank 
1945-7928
2
0.38
References 
Authors
14
3
Name
Order
Citations
PageRank
Christopher Gilliam1265.97
Thomas Kustner2336.58
T Blu32574259.70