Uncertainty Analysis In Visual Motion And Depth Estimation From Active Egomotion

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Abstract
In this paper an uncertainty analisys is performed of a system for the estimation of visual motion and depth from known egomotion. The motion strategy of the observer is constrained such as to track the point in space which projects on the image center (the fixation point) during the movement. The estimation of the optic flow is performed in two steps: firstly the velocity field is computed for each image pair at the zero crossing points; secondly the optic flow of a long sequence is obtained by matching corresponding contours between successive images. The model used is analysed and the uncertainty of each partial flow is determined on the basis of the independent parameters. The matching between image pairs causes an error propagation in the estimated velocity; a method is proposed to reduce the error using the velocity estimate relative to successive images. In this way the variance of the global flow field (both in magnitude and direction) is determined and it is used to compute the uncertainty in depth. This formulation allows to estimate the precision of the algorithm and the improvement in the accuracy of the measures, which can be achieved varying some key parameters like the number of images used. An experiment, performed on a real image sequence, is presented.

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