A fast expected time algorithm for the 2-D point pattern matching problem

2004 ◽  
Vol 37 (8) ◽  
pp. 1699-1711 ◽  
Author(s):  
P.B. Van Wamelen ◽  
Z. Li ◽  
S.S. Iyengar
Keyword(s):  
Pattern Matching ◽  
Time Algorithm ◽  
Point Pattern ◽  
Matching Problem ◽  
Point Pattern Matching ◽  
Expected Time

A new algorithm for the small-field astrometric point-pattern matching problem

2018 ◽  
Vol 72 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Cláudio P. Santiago ◽  
Carlile Lavor ◽  
Sérgio Assunção Monteiro ◽  
Alberto Kroner-Martins
Keyword(s):  
Pattern Matching ◽  
Point Pattern ◽  
Small Field ◽  
Matching Problem ◽  
Point Pattern Matching

scholarly journals Point Pattern Matching Algorithm for Planar Point Sets under Euclidean Transform

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaoyun Wang ◽  
Xianquan Zhang
Keyword(s):  
Pattern Matching ◽  
Complete Graph ◽  
Point Pattern ◽  
Point Sets ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Planar Point ◽  
Point Pattern Matching ◽  
Point Set ◽  
Pattern Matching Algorithm

Point pattern matching is an important topic of computer vision and pattern recognition. In this paper, we propose a point pattern matching algorithm for two planar point sets under Euclidean transform. We view a point set as a complete graph, establish the relation between the point set and the complete graph, and solve the point pattern matching problem by finding congruent complete graphs. Experiments are conducted to show the effectiveness and robustness of the proposed algorithm.

Combinatorial and Experimental Methods for Approximate Point Pattern Matching

Algorithmica ◽  
2003 ◽  
Vol 38 (1) ◽  
pp. 59-90 ◽  
Author(s):  
Martin Gavrilov ◽  
Piotr Indyk ◽  
Rajeev Motwani ◽  
Suresh Venkatasubramanian
Keyword(s):  
Pattern Matching ◽  
Experimental Methods ◽  
Point Pattern ◽  
Point Pattern Matching

Point pattern matching using convex hull edges

1985 ◽  
Vol SMC-15 (5) ◽  
pp. 631-637 ◽  
Author(s):  
Ardeshir Goshtasby ◽  
George C. Stockman
Keyword(s):  
Convex Hull ◽  
Pattern Matching ◽  
Point Pattern ◽  
Point Pattern Matching

scholarly journals 3D point pattern matching based on spatial geometric flexibility

2010 ◽  
Vol 7 (1) ◽  
pp. 231-246 ◽  
Author(s):  
Xiaopeng Wei ◽  
Xiaoyong Fang ◽  
Qiang Zhang ◽  
Dongsheng Zhou
Keyword(s):  
Pattern Matching ◽  
Spatial Information ◽  
Local Deformation ◽  
Point Pattern ◽  
Similar Distribution ◽  
Point Sets ◽  
Point Pattern Matching ◽  
Rigid Deformation ◽  
Optical Motion ◽  
Optical Motion Capture

We propose a new method for matching two 3D point sets of identical cardinality with global similarity but local non-rigid deformations and distribution errors. This problem arises from marker based optical motion capture (Mocap) systems for facial Mocap data. To establish one-to-one identifications, we introduce a forward 3D point pattern matching (PPM) method based on spatial geometric flexibility, which considers a non-rigid deformation between the two point-sets. First, a model normalization algorithm based on simple rules is presented to normalize the two point-sets into a fixed space. Second, a facial topological structure model is constructed, which is used to preserve spatial information for each FP. Finally, we introduce a Local Deformation Matrix (LDM) to rectify local searching vector to meet the local deformation. Experimental results confirm that this method is applicable for robust 3D point pattern matching of sparse point sets with underlying non-rigid deformation and similar distribution.

Some Experiments in Point Pattern Matching

1978 ◽  
Author(s):  
Daryl J. Kahl ◽  
Azriel Rosenfeld ◽  
Alan Danker
Keyword(s):  
Pattern Matching ◽  
Point Pattern ◽  
Point Pattern Matching

Point Pattern Matching by Relaxation

1978 ◽  
Author(s):  
Sanjay Ranade ◽  
Azriel Rosenfeld
Keyword(s):  
Pattern Matching ◽  
Point Pattern ◽  
Point Pattern Matching
Sign in / Sign up

Export Citation Format

Share Document