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
fDate :
Aug. 30 2006-Sept. 3 2006
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260657