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Computer Vision, IEEE International Conference on (1998)
Bombay, India
Jan. 4, 1998 to Jan. 7, 1998
ISBN: 81-7319-221-9
pp: 979
Sándor Fejes , University of Maryland at College Park
Larry S. Davis , University of Maryland at College Park
The dimensionality of visual motion analysis can be reduced by analyzing projections of flow vector fields. In contrast to motion vector fields, these projections exhibit simple geometric properties which are invariant to the scene structure and depend only on the camera motion. Using these properties, structure and motion can be either completely or partially decoupled. We estimate motion parameters from projections of flow fields by using robust techniques, implemented in a recursive observer model. The model is applicable to general camera motion and to large field of view and requires no point correspondence. We demonstrate our projection method on the problem of detecting independently moving objects from a moving camera. Using the projection approach, the problem can be reduced to a one-dimensional optimization process which involves robust line-fitting and outlier detection. Instantaneous detection measurements are integrated temporally using tracking and spatially applying grouping of coherently moving points.
Egomotion estimation, Detection of moving objects, Robust line fitting, Spatio-temporal integration

S. Fejes and L. S. Davis, "What Can Projections of Flow Fields Tell Us About the Visual Motion," Computer Vision, IEEE International Conference on(ICCV), Bombay, India, 1998, pp. 979.
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