Motion flow estimation from image sequences with applications to biological growth and motility

被引：3

作者：

Dong, Gang ^{[1
]}

Baskin, Tobias I. ^{[1
]}

Palaniappan, Kannappan ^{[2
]}

机构：

[1] Univ Massachusetts, Dept Biol, Amherst, MA 01003 USA

[2] Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年

关键词：

image motion analysis; velocity measurement; biological cells;

D O I：

10.1109/ICIP.2006.312551

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1245 / +

页数：3

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