Browsing by Author "Chiu, JM"

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3-D polyhedral face computation from two perspective views with the aid of a calibration plate
(1997-04-01)
Chiu, JM
;
Chen, Z
;
Wang, CM
;
資訊科學與工程研究所
;
Institute of Computer Science and Engineering
The 3-D reconstruction of visible polyhedral faces from a pair of general perspective views with the aid of a calibration plate is addressed. A polyhedron is placed on a planar calibration plate and two side views of both the polyhedron and the calibration plate are taken. Through proper arrangements we may assume that in the two views a number of polyhedral edges lying on the calibration plate and the whole calibration plate boundary are visible. We present an on-line camera calibration technique with the aid of the calibration plate and a two-stage process to find the vertex/edge correspondences without encountering the ambiguity problem of the conventional epipolar line technique. Then we give a closed form solution to the 3-D polyhedral vertices visible in both images. We also describe other advantages of using our method for the 3-D polyhedron reconstruction. Experimental results show that the obtained 3-D polyhedral vertex coordinates are rather accurate.
Determination of feature correspondences in stereo images using a calibration polygon
(1997-09-01)
Chiu, JM
;
Chen, Z
;
Chuang, JH
;
Chia, TL
;
資訊科學與工程研究所
In this paper, we propose a novel approach to solving the vertex/edge correspondence problem for stereo images. Assume an object is placed on a calibration plate (C-plate) and two perspective views of them are given. The C-plate vertex correspondence, determined by cross-ratios, is used to reduce the search space for determining object vertex/edge correspondence. First, the correspondence of object edges lying on the C-plate (called the object base edges) is considered. This is because the subpolygons obtained from the division of the C-plate by the extended line of each of these base edges are viewpoint invariant, i.e. the cross-ratio of each of their vertices in different images will have equal value. Assume that at least one of the base edges is visible in each image. Since a visible object base edge has to be an object boundary edge in an image, only object boundary edges will be considered for the cross-ratios check for the associated subpolygons as well as other geometric constraint checks in determining the object base vertex/edge correspondence. These geometric constraints include (i) the position of the edges along the boundary of object faces, and (ii) the division of the C-plate vertices by the extended lines of these edges. Based on one of the determined corresponding base edge pairs, the correspondence of all other edges can be determined by constraints similar to (i). Finally, some additional viewpoint invariant measures about the object faces and the C-plates are introduced to resolve the ambiguity problem which may arise for specific viewpoints and some special object shapes. The proposed approach only needs 2-D image data and has no constraint on the number of vertices of an object face. Experimental results are presented for some polyhedral as well as curved objects. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.
Obtaining base edge correspondence in stereo images via quantitative measures along C-diagonals
(1997-01-01)
Chuang, JH
;
Chiu, JM
;
Chen, Z
;
資訊工程學系
;
Department of Computer Science
We propose a novel approach to solving the object edge correspondence problem for stereo images. For an object placed on a calibration plate (C-plate), the proposed approach first obtains the correspondences of the object edges lying on the C-plate (the base edges) via quantitative measures of locations of the intersections of the extended line of the edges and the diagonals of the C-plate (C-diagonals) using cross ratios. The measures an viewpoint invariant for an object base edge, and are expressed in the number of image pixels. Special cases which need only coarse calculations, as well as those which require extra measures for additional point features, are also considered, The proposed approach requires 2-D image data only, and is robust in the presence of errors in the feature detection. Experimental results are presented for polyhedral and curved objects to demonstrate the effectiveness of the proposed approach. (C) 1997 Elsevier Science B.V.