DocumentCode
3125785
Title
Automated Tracking of Multiple C. Elegans
Author
Fontaine, Ebraheem ; Burdick, Joel ; Barr, Alan
Author_Institution
Dept. of Mech. Eng., California Inst. of Technol., Pasadena, CA
fYear
2006
fDate
Aug. 30 2006-Sept. 3 2006
Firstpage
3716
Lastpage
3719
Abstract
This paper presents a method for model based automated tracking of multiple worm-like creatures. These methods are essential for accurate quantitative analysis into the genetic basis of behavior that involve more than one organism. An accurate worm model is designed using the geometry of planar curves and nonlinear estimation of the model´s parameters are performed using a central difference Kalman filter (CDKF). The filter can naturally be expanded to estimate the locations of multiple worms and determine when they are occluding each other. The predicted location of the models at each iteration allows for an efficient method to determine the regions that are undergoing occlusions. Experiments on actual C. Elegans mating sequence data demonstrate the quality of the proposed method
Keywords
Kalman filters; behavioural sciences; biology computing; biomechanics; cellular biophysics; genetics; iterative methods; nonlinear estimation; zoology; C. Elegans mating sequence data; Caenorhabditis elegans; automated tracking algorithm; central difference Kalman filter; gene-behavior relationship; genetics; iteration; multiple worm-like creature; nonlinear estimation; quantitative analysis; Cities and towns; Computer science; Computer worms; Genetics; Kinematics; Mechanical engineering; Organisms; Solid modeling; Tracking; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location
New York, NY
ISSN
1557-170X
Print_ISBN
1-4244-0032-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2006.260657
Filename
4462606
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