Enhanced motion parameters estimation for an active vision system

被引：2

作者：

Shafik M. ^{[1
]}

Mertsching B. ^{[1
]}

机构：

[1] GET Lab., Paderborn University, Paderborn 33098

来源：

Pattern Recogn. Image Anal. | 2008年 / 3卷 / 370-375期

关键词：

Root Mean Square Error; Motion Vector; Motion Parameter; Segmentation Process; Motion Vector Field;

D O I：

10.1134/S1054661808030024

中图分类号：

学科分类号：

摘要：

In this paper, we present an enhanced approach for estimating 3D motion parameters from 2D motion vector fields. The proposed method achieves valuable reduction in computational time and shows high robustness against noise in the input data. The output of the algorithm is part in a multiobject segmentation approach implemented in an active vision system. Hence, the improvement in the motion parameters estimation process leads to speed-up in the overall segmentation process. © 2008 Pleiades Publishing, Ltd.

引用

页码：370 / 375

页数：5

共 13 条

[1]

Aziz Z., Mertsching B., An attentional approach for perceptual grouping of spatially distributed patterns, 29th Annual Symposium of the German Association for Pattern Recognition, DAGM 07, (2007)

[2]

Aziz Z., Mertsching B., Shafik M., Stemmer R., Evaluation of visual attention models for robots, IEEE ICVS, 2006

[3]

Ali I., Aziz Z., Mertsching B., Design issues for multi-modal attention in autonomous robot systems, International Conference on Spatial Cognition, 2006

[4]

Hajder L., Chetverikov D., Robust 3D issues for multi-modal attention in autonomous robot systems, ICCV Workshop on Dynamical Vision, Beijing, 2005

[5]

Sekkati H., Mitiche A., Joint Optical Flow Estimation, Segmentation, and 3D Interpretation with Level Sets, Computer Vision and Image Understanding, 103, pp. 89-100, (2006)

[6]

Massad A., Jesikiewicz M., Mertsching B., Space-variant motion analysis for an active-vision system, Proceedings of ACIVS 2002, Ghent, Belgium, 2002

[7]

Su Y., Sun M.T., Hsu V., Global Motion Estimation from Coarsely Sampled Motion Vector Field and the Applications, IEEE Trans. Circuits Syst. Video Techn., 15, pp. 232-242, (2005)

[8]

Fang J.-Q., Huang T.S., Solving Three-Dimensional Small-Rotation Motion Equations: Uniqueness, Algorithms, and Numerical Results, Computer Vision, Graphics, and Image Processing, 26, pp. 183-206, (1984)

[9]

Longuet-Higgins H.C., Prazdny K., The Interpretation of a Moving Retinal Image, Proc. R. Soc. (London), Ser. B, 208, pp. 385-397, (1981)

[10]

Adiv G., Determining Three-Dimensional Motion and Structure from Optical Flow Generated by Several Moving Objects, IEEE Trans. Pattern Anal. Machine Intell., PAMI-7, pp. 348-401, (1985)

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