DocumentCode :
2490651
Title :
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
Link To Document :
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