ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:TA-L5.5
Session:Motion Estimation
Time:Tuesday, October 10, 11:20 - 11:40
Presentation: Lecture
Topic: Motion Detection and Estimation: Optical flow
Title: MOTION FLOW ESTIMATION FROM IMAGE SEQUENCES WITH APPLICATIONS TO BIOLOGICAL GROWTH AND MOTILITY
Authors: Gang Dong; University of Massachusetts 
 Tobias Baskin; University of Massachusetts 
 Kannappan Palaniappan; University of Missouri, Columbia 
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.