Binocular Image Flows: Steps Toward Stereo-Motion Fusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determining Object Translation Information Using Stereoscopic Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Flow Segmentation and Estimation by Constraint Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust, Real-Time Motion Estimation from Long Image Sequences Using Kalman Filtering
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Acquisition of translational motion by the parallel trinocular
Information Sciences: an International Journal
Image and Vision Computing
Servo tracking of three-dimensional motion by the parallel trinocular
WSEAS Transactions on Systems and Control
Quasi-Parallax for Nearly Parallel Frontal Eyes
International Journal of Computer Vision
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Image flow fields from parallel stereo cameras are analyzed to determine the relative 3-D translational motion of the camera platform with respect to objects in view and to establish stereo correspondence of features in the left and right images. A two-step procedure is suggested. In the first step, translational motion parameters are determined from linear equations the coefficients of which consist of the sums of measured quantities in the two images. Separate equations are developed for cases when measurements of either the full optical flow or the normal flow are available. This computation does not require feature-to-feature correspondence. In addition, no assumption is made about the surfaces being viewed. In the second step of the calculation, with the knowledge of the estimated translational motion parameters, the binocular flow information is used to find features in one image that correspond to given features in the other image. Experimental results with synthetic and laboratory images indicate that the method provides accurate results even in the presence of noise.