DocumentCode
1768706
Title
Designing of the input filter group of the multichannel optical flow estimate method
Author
Morimitsu, Marina ; Yamaguchi, Toru ; Harada, Hiroshi
Author_Institution
Grad. Sch. of Sci. & Technol., Kumamoto Univ., Kumamoto, Japan
fYear
2014
fDate
22-25 Oct. 2014
Firstpage
1070
Lastpage
1075
Abstract
Spatio-temporal derivative method is one of the most effective methods of determining the velocity of moving objects. This method shows excellent response, but it has a problem that estimated velocity is not accurate where Hessian of the target pattern is small or there is noise on the image. It has been reported that one can obtain more stable velocity vectors by synthesizing the velocity vectors obtained for each channel that is consist of different characteristic filters. However, guidelines for the choice of optimal filter group has not been established yet. Therefore, in this study, we researched to suppress unstable velocity vectors at motion edge by using compact filter group. In particular, we made some filter group which consists of different characteristic (passband) filters, and applying it to various image sequences. Then, we searched for the filter group that can provide stable velocity vectors at motion edge on the image. We compared the results in case where filter coefficient is original and normalized. It was found that stable velocity vector can be obtained by applying normalized coefficient filters.
Keywords
Hessian matrices; image sequences; robot vision; Hessian; compact filter group; different characteristic filters; filter coefficient; image sequences; input filter group; motion edge; multichannel optical flow estimate method; passband filters; robot vision; spatio-temporal derivative method; stable velocity vectors; Vectors; Spatio-temporal differentiation; multichannel; optical flow; robot vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems (ICCAS), 2014 14th International Conference on
Conference_Location
Seoul
ISSN
2093-7121
Print_ISBN
978-8-9932-1506-9
Type
conf
DOI
10.1109/ICCAS.2014.6987935
Filename
6987935
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