Noise sensitivity analysis of statistically consistent optimal structure from motion

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, th...

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Bibliographic Details
Main Authors: Park, R.C., Byungsoo Park, Munsang Kim, Mishra, B.
Format: Conference Proceeding
Language:English
Subjects:
Additive noise
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Fluid flow measurement
Image motion analysis
Motion analysis
Motion measurement
Noise measurement
Optical noise
Optical sensors
Sensitivity analysis
Shape measurement
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Description
Summary: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.
DOI:10.1109/IROS.2004.1389990