Title :
Motion Flow Estimation from Image Sequences with Applications to Biological Growth and Motility
Author :
Dong, Ganggang ; Baskin, T.I. ; Palaniappan, Kannappan
Author_Institution :
Dept. of Biol., Massachusetts Univ., Amherst, MA, USA
Abstract :
In this paper, a new method for motion flow estimation that considers errors in all the derivative measurements is presented. Based on the total least squares (TLS) model, we accurately estimate the motion flow in the general noise case by combining noise model (in form of covariance matrix) with a parametric motion model. The proposed algorithm is tested on two different types of biological motion, a growing plant root and a gastrulating embryo, with sequences obtained microscopically. The local, instantaneous velocity field estimated by the algorithm reveals the behavior of the underlying cellular elements.
Keywords :
biological techniques; biology computing; cell motility; image sequences; least squares approximations; motion estimation; biological growth-motility; cellular element; image sequence; motion flow estimation; noise model; total least squares model; Biological system modeling; Covariance matrix; Estimation error; Fluid flow measurement; Image sequences; Least squares approximation; Motion estimation; Motion measurement; Plants (biology); Testing; biological cells; image motion analysis; velocity measurement;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312551
