Noise sensitivity analysis of statistically consistent optimal structure from motion

Author

Park, EC ; Byungsoo Park ; Kim, Munsang ; Mishra, Bhubaneswar

Author_Institution

Mech. & Aerosp. Eng., Seoul Nat. Univ., South Korea

Volume

4

fYear

2004

fDate

28 Sept.-2 Oct. 2004

Firstpage

3698

Abstract

We present a noise sensitivity analysis of the differential optimal structure from motion problem. Given optical flow measurements for a set of feature points, we formulate a least squares cost function based on a more reasonable additive isotropic model of measurement noise, normalized by depth, that also leads to statistically consistent estimates of the shape and motion parameters. A cyclic coordinate descent algorithm is developed, and its performance examined through experiments.

Keywords

feature extraction; image sequences; least mean squares methods; motion estimation; noise measurement; optimisation; sensitivity analysis; statistical analysis; additive isotropic model; differential optimal structure; least squares cost function; motion problem; noise sensitivity analysis; optical flow measurements; statistical analysis; Additive noise; Fluid flow measurement; Image motion analysis; Motion analysis; Motion measurement; Noise measurement; Optical noise; Optical sensors; Sensitivity analysis; Shape measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on

Print_ISBN

0-7803-8463-6

Type

conf

DOI

10.1109/IROS.2004.1389990

Filename

1389990