MOTION PARAMETER-ESTIMATION BY TRACKING STATIONARY 3-DIMENSIONAL STRAIGHT-LINES IN IMAGE SEQUENCES

The purpose of this work is to utilize extracted linear features from imagery collected by a Mobile Mapping System (MMS) for the purpose of motion parameter estimation. The MMS is assumed to be equipped with tw o or more cameras. The relative relationship between these cameras is rigid, i.e. it does not change from one epoch to the other and can be determined by a calibration procedure. An optimal (minimal) representa tion of 3-D straight lines that requires only four parameters is discu ssed. The perspective transformation of the extracted linear features back and forth between image and object space is derived. By tracking stationary linear features in successive image sequences, the motion p arameters, rotation and displacement, between the system's position at the corresponding epochs can be estimated. The suggested algorithm wo rks as follows. First, straight-line features are extracted from the i magery. Then, a model space coordinate system is defined for each syst em position at which an image set is collected. The origin of this sys tem can be chosen as the perspective center of one of the cameras onbo ard. Then, the linear features in successive image sets are projected into the corresponding model space. It has to be noted that the projec tion procedure is performed separately for the image sets under consid eration. The mathematical model that relates the parameters of the res ulting conjugate lines to the motion parameters of the system is deriv ed. The relationship is obtained by imposing four constraints on the f our degrees of freedom of any conjugate Lines. The suggested algorithm is used to estimate the motion parameters using conjugate linear feat ures in successive stereo-pairs collected by the GPS van of the Ohio S tate University. This algorithm will be helpful in deriving the motion parameters of the vehicle during periods of failure of the positionin g component onboard, e.g. GPS loss of lock for a long time interval. ( C) 1998 Elsevier Science B.V. All rights reserved.