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
收藏
页码：1245 / +
页数：3
相关论文
共 50 条
  • [21] Robust motion estimation for calibrated cameras from monocular image sequences
    Wagner, R
    Liu, FY
    Donner, K
    COMPUTER VISION AND IMAGE UNDERSTANDING, 1999, 73 (02) : 258 - 268
  • [22] Stochastic modeling and entropy constrained estimation of motion from image sequences
    Servetto, SD
    Podilchuk, CI
    1998 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL 3, 1998, : 591 - 595
  • [23] Contour motion estimation from image sequences using curvature information
    Park, JS
    Han, JH
    PATTERN RECOGNITION, 1998, 31 (01) : 31 - 39
  • [24] Image Sequence Denoising with Motion Estimation in Color Image Sequences
    Sarode, Milindkumar V.
    Deshmukh, Prashant R.
    ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2011, 1 (06) : 139 - 143
  • [25] Reconstruction from planar motion image sequences with applications for autonomous vehicles
    Stewénius, H
    Oskarsson, M
    Åström, K
    IMAGE ANALYSIS, PROCEEDINGS, 2005, 3540 : 609 - 618
  • [26] Denoising image sequences does not require motion estimation
    Buades, A
    Coll, B
    Morel, JM
    AVSS 2005: ADVANCED VIDEO AND SIGNAL BASED SURVEILLANCE, PROCEEDINGS, 2005, : 70 - 74
  • [27] RECURSIVE-BATCH ESTIMATION OF MOTION AND STRUCTURE FROM MONOCULAR IMAGE SEQUENCES
    CUI, N
    WENG, JJ
    COHEN, P
    CVGIP-IMAGE UNDERSTANDING, 1994, 59 (02): : 154 - 170
  • [28] Optimal schemes for motion estimation on colour image sequences
    Magarey, J
    Kokaram, A
    Lingsbury, N
    INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL II, 1997, : 187 - 190
  • [29] Cardiac Motion Estimation with Coronary Angiographic Image Sequences
    Sun, Zheng
    Bai, Hua
    GREEN POWER, MATERIALS AND MANUFACTURING TECHNOLOGY AND APPLICATIONS II, 2012, 214 : 108 - 113
  • [30] Motion estimation and compensation from noisy image sequences: A new filtering scheme
    Benmoussat, Nawal
    Belbachir, M. Faouzi
    Benamar, Beloufa
    IMAGE AND VISION COMPUTING, 2007, 25 (05) : 686 - 694
12345