Recognition for 3‐D objects based on the determination of the position and the orientation from a noisy single perspective view
Jim Z.C. Lai · Journal of the Chinese Institute of Engineers · 1993
Recognizing 3‐D objects from 2‐D images has been an important area of research in computer vision. In this paper, an efficient method is developed to determine the position and the orientation of a 3‐D polyhedron in a noisy image. This method assumes that the direction of a straight line on an image can be determined from noisy data. A set of linear equations are used to determine the orientation of an object. In cases where there are not enough straight lines of an image presented, the constraint equations can be introduced and the iterative process is applied. However the iterative process is simple and the divergence is not a problem. After the orientation is determined, the straight lines, corresponding to the visible edges of the object, are used to determine the intersection points. From the intersections and the corresponding corners of the polyhedron, another set of linear equations are used to obtain the position of the object. If the sum of the perpendicular distances, between the endpoints of the image projection of each model line and the corresponding image line, divided by the number of end‐points is less than a threshold, then the matching process is passed. It is shown, in this paper, that we cannot distinguish between geometrically similar objects without texture analysis from a single perspective view. Thus, the threshold, ϵi , which is determined by a scheme developed here, of model i is used to check whether the candidate model is accepted. Finally, all the concepts, presented in this paper, are illustrated through several examples given in this paper.