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Motion from Fixation

Soatto, Stefano and Perona, Pietro (1995) Motion from Fixation. California Institute of Technology , Pasadena, CA. (Unpublished)

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We study the problem of estimating rigid motion from a sequence of monocular perspective images obtained by navigating around an object while fixating a particular feature point. The motivation comes from the mechanics of the buman eye, which either pursuits smoothly some fixation point in the scene, or "saccades" between different fixation points. In particular, we are interested in understanding whether fixation helps the process of estimating motion in the sense that it makes it more robust, better conditioned or simpler to solve. We cast the problem in the framework of "dynamic epipolar geometry", and propose an implicit dynamical model for recursively estimating motion from fixation. This allows us to compare directly the quality of the estimates of motion obtained by imposing the fixation constraint, or by assuming a general rigid motion, simply by changing the geometry of the parameter space while maintaining the same structure of the recursive estimator. We also present a closed-form static solution from two views, and a recursive estimator of the absolute attitude between the viewer and the scene. One important issue is how do the estimates degrade in presence of disturbances in the tracking procedure. We describe a simple fixation control that converges exponentially, which is complemented by a image shift-registration for achieving sub-pixel accuracy, and assess how small deviations from perfect tracking affect the estimates of motion.

Item Type:Report or Paper (Technical Report)
Perona, Pietro0000-0002-7583-5809
Additional Information:Research sponsored by NSF NYI Award, NSF ERC in Neuromorphic Systems Engineering at Caltech, ONR grant N00014-93-1-0990. This work is registered as CDS technical report no. CIT-CDS 95-006, February 1995.
Group:Control and Dynamical Systems Technical Reports
Record Number:CaltechCDSTR:1995.006
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Usage Policy:You are granted permission for individual, educational, research and non-commercial reproduction, distribution, display and performance of this work in any format.
ID Code:28087
Deposited By: Imported from CaltechCDSTR
Deposited On:19 Sep 2006
Last Modified:03 Oct 2019 03:29

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