Paper Info
Title
A Sparse-To-Dense Method For 3d Optical Flow Estimation In 3d Light-Microscopy Image Sequences
Abstract
We present a two-stage 3D optical flow estimation method for light microscopy image volumes. The method takes a pair of light microscopy image volumes as input, segments the 2D slices of the source volume in superpixels and sparsely estimates the 3D displacement vectors in the volume pair. A weighted interpolation is then introduced to get a dense 3D flow field. Edges and motion boundaries are considered during the interpolation. Our experimental results show good gain in execution speed, and accuracy evaluated in computer generated 3D data. Promising results on real 3D image sequences are reported.
Year
Venue
Keywords
2018
2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018)
3D PatchMatch, Interpolation, Fluorescence Microscopy, 3D Optical Flow
Field
DocType
ISSN
Computer vision,Computer science,Flow (psychology),Interpolation,Optical flow estimation,Artificial intelligence,Microscopy,3d image
Conference
1945-7928
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Sandeep Manandhar100.68
Patrick Bouthemy22675286.70
Erik S Welf321.26
Philippe Roudot462.29
Charles Kervrann593467.36