Paper Info
Title
Illumination Invariant Motion Estimation and Segmentation.
Abstract
Extracting moving objects from their background or partitioning them have been one of the most prerequisite tasks for various computer vision applications such as surveillance, tracking, human machine interface. etc. Though many previous approaches have been working in a certain level, still they are not robust under various unexpected situation such as large illumination change. In this paper. we propose a motion segmentation method based on our robust illumination invariant optical flow estimation. We present the superiority of our motion estimation method with synthesized images and improved segmentation results with real images.
Year
DOI
Venue
2011
10.1007/978-3-642-27186-1_10
Communications in Computer and Information Science
Keywords
Field
DocType
Motion estimation,Optical flow,Segmentation,Illumination invariant
Computer vision,Scale-space segmentation,Segmentation,Computer science,Optical flow estimation,Artificial intelligence,Invariant (mathematics),Human–machine interface,Real image,Motion estimation,Optical flow
Conference
Volume
ISSN
Citations 
263
1865-0929
0
PageRank 
References 
Authors
0.34
14
2
Name
Order
Citations
PageRank
Yeonho Kim112110.69
Soo-Yeong Yi2306.92