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- W2301472619 abstract "A theory for the interpretation of visual motion for a moving observer is developed and presented. At the center of the thesis is the Collinear Point Constraint, which permits cancellation of observer rotation while simultaneously constraining the translational direction. Then, a sufficient number of constraints permits the translational direction to be computed. This step of the algorithm is implemented via a focus of Expansion (FOE) operator which is convolved with the image motion input. This step is found to be very robust to noise in the input.Next, independent motion is detected for situations where the independent motion has not corrupted the FOE computation. After detecting independent motion, shape can be computed. However, first the rotation parameters are computed, to provide a more robust shape estimate. Computing rotation is a linear least squares estimation problem once the direction of translation is known. However, since the noise in the velocity estimates that would be used in the least squares computation is not typically purely Gaussian with zero mean, a subset of measurements that have less noise is used. This subset is found using a robust estimation procedure, that uses the known direction of translation and the Collinear Point Constraint. Once this subset is found, rotation and then shape can be computed easily.Lastly, extensions are presented. These include an algorithm that can detect some types of independent motion before the direction of translation is computed, an extension of orthographic projection, discontinuity detection, and temporal extensions using a Kalman filter." @default.
- W2301472619 created "2016-06-24" @default.
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- W2301472619 date "1993-01-02" @default.
- W2301472619 modified "2023-09-27" @default.
- W2301472619 title "Computing egomotion, shape and detecting independent motion from image motion" @default.
- W2301472619 hasPublicationYear "1993" @default.
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