TY - JOUR
T1 - Geometric pattern matching under Euclidean motion
AU - Chew, L. Paul
AU - Goodrich, Michael T.
AU - Huttenlochera, Daniel P.
AU - Kedem, Klara
AU - Kleinberg, Jon M.
AU - Kravets, Dina
N1 - Funding Information:
* Corresponding author. l This work was supported by the Advanced Research Projects Agency of the Department of Defense under ONR Contract N00014-92-J-1989, and by ONR Contract N00014-92-J-1839, NSF Contract IRI-9006137, and AFOSR Contract AFOSR-91-0328. 2 This work was supported by the NSF and DARPA under Grant CCR-8908092, and by the NSF under Grants CCR-9003299 and IRI-9116843. 3 This work was supported in part by NSF grant IRI-9057928 and matching funds from Kodak, General Electric, and Xerox, and in part by US Air Force contract AFOSR-91-0328. 4 This work was also supported by the Eshkol grant 04601-90 from The Israeli Ministry of Science and Technology, s This work was supported in part by the Air Force under Contract AFOSR-89-0271 and by the Defense Advanced Research Projects Agency under Contracts N00014-87-K-825 and N00014-89-J-1988.
PY - 1997/1/1
Y1 - 1997/1/1
N2 - Given two planar sets A and B, we examine the problem of determining the smallest ε such that there is a Euclidean motion (rotation and translation) of A that brings each member of A within distance ε of some member of B. We establish upper bounds on the combinatorial complexity of this subproblem in model-based computer vision, when the sets A and B contain points, line segments, or (filled-in) polygons. We also show how to use our methods to substantially improve on existing algorithms for finding the minimum Hausdorff distance under Euclidean motion.
AB - Given two planar sets A and B, we examine the problem of determining the smallest ε such that there is a Euclidean motion (rotation and translation) of A that brings each member of A within distance ε of some member of B. We establish upper bounds on the combinatorial complexity of this subproblem in model-based computer vision, when the sets A and B contain points, line segments, or (filled-in) polygons. We also show how to use our methods to substantially improve on existing algorithms for finding the minimum Hausdorff distance under Euclidean motion.
UR - http://www.scopus.com/inward/record.url?scp=0001532918&partnerID=8YFLogxK
U2 - 10.1016/0925-7721(95)00047-X
DO - 10.1016/0925-7721(95)00047-X
M3 - Article
AN - SCOPUS:0001532918
SN - 0925-7721
VL - 7
SP - 113
EP - 124
JO - Computational Geometry: Theory and Applications
JF - Computational Geometry: Theory and Applications
IS - 1-2
ER -