Paper Info
Title
Possibility Theory and Rough Histograms for Motion Estimation in a Video Sequence
Abstract
This article proposes to use both theories of possibility and rough histograms to deal with estimation of the movement between two images in a video sequence. A fuzzy modeling of data and a reasoning based on imprecise statistics allow us to partly cope with the constraints associated to classical movement estimation methods such as correlation or optical flow based-methods. The theoretical aspect of our method will be explained in details, and its properties will be shown. An illustrative example will also be presented.
Year
DOI
Venue
2001
10.1007/3-540-45129-3_43
IWVF
Keywords
Field
DocType
video sequence,illustrative example,optical flow based-methods,imprecise statistic,rough histogram,rough histograms,motion estimation,theoretical aspect,possibility theory,fuzzy modeling,classical movement estimation method,optical flow
Histogram,Computer science,Fuzzy logic,Algorithm,Possibility theory,Artificial intelligence,Motion estimation,Fuzzy number,Membership function,Optical flow,Distributed computing,Statistical analysis
Conference
ISBN
Citations 
PageRank 
3-540-42120-3
2
0.48
References 
Authors
5
3
Name
Order
Citations
PageRank
Frederic Comby17311.55
O. Strauss215321.17
Marie-José Aldon314711.61