scholarly journals Connectivity of Matching Graph of Hypercube

2009 ◽  
Vol 23 (2) ◽  
pp. 1100-1109 ◽  
Author(s):  
Jiří Fink
Keyword(s):  
Matching Graph

On the perfect matching graph defined by a set of cycles

2015 ◽  
Vol 23 (2) ◽  
pp. 549-556
Author(s):  
Ana Paulina Figueroa ◽  
Julián Fresán-Figueroa ◽  
Eduardo Rivera-Campo
Keyword(s):  
Perfect Matching ◽  
Matching Graph

scholarly journals Second kind maximum matching graph

2014 ◽  
Vol 323 ◽  
pp. 27-34 ◽  
Author(s):  
Yan Liu ◽  
Zhengbiao Liu
Keyword(s):  
Maximum Matching ◽  
Matching Graph

scholarly journals A semi-automatic tool to georeference historical landscape images

2018 ◽  
Author(s):  
Nicolas Blanc ◽  
Timothée Produit ◽  
Jens Ingensand
Keyword(s):  
Reference Image ◽  
Automatic Process ◽  
Query Image ◽  
Web Based ◽  
Virtual Globe ◽  
Matching Process ◽  
Digital Elevation ◽  
Matching Graph ◽  
Automatic Tool ◽  
Elevation Model

Smapshot is a web-based participatory virtual globe where users can georeference historical images of the landscape by clicking a minimum of six well identifiable correspondence points between the image and a 3D virtual globe. The images database is expected to grow exponentially. In a near future, the work of the web users will no longer be enough. To tackle this issue, we developed a semi-automatic process to georeference images. The volunteers will be shown only images having a maximum number of neighbour images in the matching graph. These neighbour images are the ones with which they share some overlay. This overlap is detected using the SIFT algorithm in a pairewise matching process. For an image pair made of a reference image with a known pose and a query image we want to georeference, we extracted the 3D world coordinates of the tie points from a digital elevation model. Then, by running a perspective-n-point algorithm after having geometrically tested the resulting homography between the two images, we compute the 6 degree of freedom pose, i.e. the position (X,Y,Z) and orientation (azimuth, tilt and roll angles) of the query image. The query image then becomes a reference and the georeference computation can be propagated more deeply in the graph structure.

scholarly journals A semi-automatic tool to georeference historical landscape images

2018 ◽  
Author(s):  
Nicolas Blanc ◽  
Timothée Produit ◽  
Jens Ingensand
Keyword(s):  
Reference Image ◽  
Automatic Process ◽  
Query Image ◽  
Web Based ◽  
Virtual Globe ◽  
Matching Process ◽  
Digital Elevation ◽  
Matching Graph ◽  
Automatic Tool ◽  
Elevation Model

Smapshot is a web-based participatory virtual globe where users can georeference historical images of the landscape by clicking a minimum of six well identifiable correspondence points between the image and a 3D virtual globe. The images database is expected to grow exponentially. In a near future, the work of the web users will no longer be enough. To tackle this issue, we developed a semi-automatic process to georeference images. The volunteers will be shown only images having a maximum number of neighbour images in the matching graph. These neighbour images are the ones with which they share some overlay. This overlap is detected using the SIFT algorithm in a pairewise matching process. For an image pair made of a reference image with a known pose and a query image we want to georeference, we extracted the 3D world coordinates of the tie points from a digital elevation model. Then, by running a perspective-n-point algorithm after having geometrically tested the resulting homography between the two images, we compute the 6 degree of freedom pose, i.e. the position (X,Y,Z) and orientation (azimuth, tilt and roll angles) of the query image. The query image then becomes a reference and the georeference computation can be propagated more deeply in the graph structure.

scholarly journals OBJECT DETECTION AND CLASSIFICATION FROM CLUTTERED LARGE-SCALE INDOOR SCENE VIA ANCHOR-BASED GRAPH

2020 ◽  
Vol V-2-2020 ◽  
pp. 289-296
Author(s):  
F. Su ◽  
Y. Liang ◽  
Z. Gang ◽  
X. Zuo ◽  
F. Yang ◽  
...  
Keyword(s):  
Object Detection ◽  
Large Scale ◽  
Region Growing ◽  
Experimental Tests ◽  
Point Clouds ◽  
Indoor Environments ◽  
Object A ◽  
Considerable Research ◽  
Matching Graph ◽  
3D Scans

Abstract. Indoor object detection and classification from scanned point clouds has recently attracted considerable research interest. However, detecting and classifying objects with arbitrary upward orientation has emerged as a substantial challenge. This paper presents an anchor-based graph method via geometric and topological similarity among indoor objects. With this method, the misclassification that usually occurs in the objects placed non-vertical with the floor is overcome by extracting anchor in each graph via nodes’ geometric attribute and by matching graph via topological relationship between nodes and anchor, rather than the features along the upward orientation. A region growing-based method along the anchor’s upward orientation is proposed for classifying the unlabeled over-segmentation parts. Such an anchor-based method ensures both the accuracy of object classification and the geometric integrity of object. A series of experimental tests using three real-world 3D scans of indoor environments show the effectiveness and feasibility of the proposed method.

RULE BASED EXPERT SYSTEM SHELLS—NEW SOFTWARE TOOLS FOR PATTERN RECOGNITION?

1989 ◽  
Vol 03 (01) ◽  
pp. 85-102
Author(s):  
H. BUNKE ◽  
J. DVORAK
Keyword(s):  
Pattern Recognition ◽  
Expert System ◽  
Programming Languages ◽  
Graph Matching ◽  
Finite State Automata ◽  
Rule Based ◽  
Finite State ◽  
Matching Graph ◽  
Procedural Programming ◽  
Context Free

In this paper, we discuss how rule based expert system shells can be used in pattern recognition for the implementation of algorithms which are procedurally oriented in their nature rather than rule based, and have traditionally been implemented in procedural programming languages. Particular examples include finite state automata, context free parsing, string matching, graph matching and discrete relaxation.

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