scholarly journals Different Sourcing Point of Interest Matching Method Considering Multiple Constraints

2020 ◽  
Vol 9 (4) ◽  
pp. 214
Author(s):  
Chengming Li ◽  
Li Liu ◽  
Zhaoxin Dai ◽  
Xiaoli Liu
Keyword(s):  
Spatial Location ◽  
Calculation Model ◽  
Matching Method ◽  
Matching Accuracy ◽  
Point Of Interest ◽  
Optimal Thresholds ◽  
Weak Constraints ◽  
Constraint Model ◽  
Dongying City ◽  
Different Sources

Point of interest (POI) matching is critical but is the most technically difficult part of multi-source POI fusion. The accurate matching of POIs from different sources is important for the effective reuse of POI data. However, the existing research on POI matching usually adopts weak constraints, which leads to a low POI matching accuracy. To address the shortcomings of previous studies, this paper proposes a POI matching method with multiple determination constraints. First, according to various attributes (name, class, and spatial location), a new calculation model considering spatial topology, name role labeling, and bottom-up class constraints is established. In addition, the optimal threshold values corresponding to the different attribute constraints are determined. Second, according to the multiattribute constraint values and optimal thresholds, a constraint model with multiple strict determination constraints is proposed. Finally, actual POI data from Baidu Map and Gaode Map in Dongying city is used to validate the method. Comparing to the existing method, the accuracy and recall of the proposed method increase 0.3% and 7.1%, respectively. The experimental results demonstrate that the proposed POI matching method attains a high matching accuracy and high feasibility.

Building a Standard 3D Face Database Based on Planar Templates

2011 ◽  
Vol 48-49 ◽  
pp. 280-283
Author(s):  
Xin Xin Li ◽  
Xun Gong
Keyword(s):  
3D Models ◽  
Face Database ◽  
Matching Method ◽  
Matching Accuracy ◽  
Point Matching ◽  
Dense Point ◽  
The Mean ◽  
Point To Point ◽  
3D Face Database ◽  
2D Space

This paper presents a new point matching method to solve the dense point-to-point alignment of scanned 3D faces. Texture maps of 3D models are generated at first by unwrapping 3D faces to 2D space. Then, we build planar templates based on the mean shape computed by a group of annotated texture map. 34 landmarks on the unwrapped texture images are located by AAM and the final correspondence is built according to the templates. Comparing to the traditional algorithms, the presented point matching method can achieve good matching accuracy and stability.

Research of Stereo Matching Based on HALCON

2013 ◽  
Vol 415 ◽  
pp. 361-364
Author(s):  
Hui Yu Xiang ◽  
Zhe Li ◽  
Jia Jun Huang ◽  
Baoan Han
Keyword(s):  
Image Matching ◽  
Stereo Matching ◽  
Vision System ◽  
Difficult Problem ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Binocular Stereo Vision ◽  
Binocular Stereo ◽  
Matching Window

Binocular stereo matching is a hot and difficult problem in machine vision. In this paper, based on the matching method of Halcon which is visual software perform image matching. First, performing binocular stereo vision system calibration, based on the calibration results acquired the epipolar standard geometric structure. Then, image matching researched under this structure. At last, using ncc matching algorithm, through comparing the different parameters matching window obtain ideal match results. Experiments prove that this method not only can effectively shorten matching time, but also can achieve higher matching accuracy.

Study on Image Matching Based on Speed up Robust Features Method

2014 ◽  
Vol 1044-1045 ◽  
pp. 1352-1356
Author(s):  
Shu Guang Wu ◽  
Shu He ◽  
Xia Yang
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Matching ◽  
Comprehensive Analysis ◽  
The Other ◽  
Matching Method ◽  
Matching Accuracy ◽  
Speed Up

Image registration is one of the fundamental problems in digital image processing, which is a prerequisite and key step for further comprehensive analysis,considering the advantages of the algorithm in speed and its disadvantage of more false matching points,a image matching method based on RANSAC and surf isproposed.The experiments results show that compared with the other algorithms,the surf algorithm improves the matching speed，as well as the matching accuracy，and exhibits good performance in terms of resisting rotation，noise,and brightness changes．

Image Matching Based on Analysis of Reliability in Log-Polar Field

2012 ◽  
Vol 532-533 ◽  
pp. 954-958
Author(s):  
Yi Ping Xu ◽  
Jing Tan ◽  
Hong Ping Li ◽  
Yan Tian
Keyword(s):  
Target Detection ◽  
Image Matching ◽  
Polar Field ◽  
Data Reliability ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Performance

Due to the invariance to scale and rotation, image matching method based on Log-Polar transformation has been extensively applied in target detection and location. This paper analyses the effect on image matching accuracy from variation of scale and rotation, and proposes a modified image matching method based on analysis of data reliability for matching, this method can eliminate the interference from invalid data and improve the image matching performance. Experiments show that this method has better performance in accuracy.

Research of an Improved Snail Image Recognition Method Based on Grayscale Template Matching

2013 ◽  
Vol 433-435 ◽  
pp. 700-704
Author(s):  
Yin E Zhang
Keyword(s):  
Template Matching ◽  
Source Image ◽  
Complex Environment ◽  
Recognition Method ◽  
Matching Method ◽  
Matching Accuracy ◽  
Matching Algorithm ◽  
Template Image ◽  
Traditional Algorithm ◽  
Template Selection

As the lack in the accuracy and speed of the template matching algorithm for the snail image in the complex environment, the snail source image and the template image have the appropriate scaling in order to improve their sizes in the traditional algorithm. The new algorithm avoids the very big and accurate characteristics about the snail images through shrinking the source images down. The grayscale template matching method is put forward based on the traditional template selection set to prevent that the error caused by human factors on the selected template, the redundancy between the templates is removed in a large extent, further the accuracy of the matching is improved, and the matching time is reduced greatly in the case of matching accuracy guarantee.

scholarly journals Entity Alignment Method of Points of Interest for Internet Location-Based Services

2020 ◽  
Vol 24 (7) ◽  
pp. 837-845
Author(s):  
Chaoran Zhou ◽  
Jianping Zhao ◽  
Xin Zhang ◽  
Chenghao Ren ◽  
◽  
...  
Keyword(s):  
Location Based Services ◽  
Geographical Information ◽  
Alignment Method ◽  
Text Data ◽  
Rating Data ◽  
Internet Applications ◽  
Point Of Interest ◽  
Data Source ◽  
Data Consolidation ◽  
Different Sources

In Internet applications, the description for the same point of interest (POI) entity for different location-based services (LBSs) is not completely identical. The POI entity information in a single LBS data source contains incomplete data and exhibits insufficient objectivity. Aligning and consolidating POI entities from various LBSs can provide users with more comprehensive, objective, and authoritative POI information. We herein propose a multi-attribute measurement-based entity alignment method for Internet LBSs to achieve POI entity alignment and data consolidation. This method is based on multi-attribute information (geographical information, text coincidence information, semantic information) of POI entities and is combined with different measurement methods to calculate the similarity of candidate entity pairs. Considering the demand for computational efficiency, the particle swarm optimization algorithm is used to train the model and optimize the weights of multi-attribute measurements. A consolidation strategy is designed for the LBS text data and user rating data from different sources to obtain more comprehensive and objective information. The experimental results show that, compared with other baseline models, the POI alignment method based on multi-attribute measurement performed the best. Using this method, the information of POI entities in multisource LBS can be integrated to serve netizens.

FINGERPRINT MINUTIAE RELATIONSHIP REPRESENTATION AND MATCHING BASED ON CURVE COORDINATE SYSTEM

2005 ◽  
Vol 05 (04) ◽  
pp. 729-744 ◽  
Author(s):  
EN ZHU ◽  
JIAN-PING YIN ◽  
GUO-MIN ZHANG ◽  
CHUN-FENG HU
Keyword(s):  
Coordinate System ◽  
Matching Method ◽  
Matching Accuracy ◽  
Fingerprint Minutiae

A minutiae relationship representation and matching method based on curve coordinate system is proposed. For each minutia, a curve coordinate system is established, and the coordinates of other minutiae in this coordinate system is computed. Thus, the coordinate relationship between each pair of minutiae can be evaluated. These relationships are used for pairing minutiae between the template fingerprint and the query fingerprint by means of transferring reference minutiae. The algorithm is tested on FVC2004DBs which include many highly distorted fingerprints. Results have shown that the proposed algorithm achieves improved matching accuracy and is able to cope with highly distorted fingerprints.

Detection and Tracking of Vehicle Target Based on Super-Resolution Reconstruction and Variable Template Matching

2014 ◽  
Vol 541-542 ◽  
pp. 1429-1432
Author(s):  
Jun Yong Ma ◽  
Shao Dong Chen ◽  
Sheng Wei Zhang
Keyword(s):  
Template Matching ◽  
Super Resolution ◽  
Image Sequence ◽  
Low Resolution ◽  
Matching Method ◽  
Matching Accuracy ◽  
High Quality ◽  
Resolution Image ◽  
Detection And Tracking ◽  
Image Super Resolution

Vehicle Target Detection and Tracking Method Based on Image Super-Resolution Reconstruction and Variable Template Matching is Put Forward. Firstly, a Nonlinear Iterative Algorithm is Applied to Reconstruct a Super-Resolution Image from Low Resolution Image Sequence; then, the Image is Standardized and the Movement Areas are Determined; Finally, the Variable Template Matching Method is Used to Detect and Track the Vehicle Targets in Movement Areas. from the Characteristics of Algorithm and the Experiment Results, we can see that the Proposed Algorithm Improves the Matching Accuracy of Target Tracking and Better Solves the Limitation of Missed Detection for Traditional Methods. the Reason of the Good Performance of the Proposed Algorithm Relies in High Quality Images Acquired by Super-Resolution Reconstruction from Low Resolution Image Sequence and the Application of Variable Template Matching Method.

Distance-Scale Restricted SIFT Matching Method for Complicated Content & Different Scales Image Pairs

2014 ◽  
Vol 526 ◽  
pp. 292-296
Author(s):  
Zhen Yu Wu ◽  
Hu Hong
Keyword(s):  
Scale Invariant Feature Transform ◽  
Matching Method ◽  
Matching Accuracy ◽  
Scale Invariant ◽  
Simple Method ◽  
Invariant Feature ◽  
Matching Performance ◽  
Feature Transform ◽  
Image Pairs ◽  
Scale Invariant Feature

Scale invariant feature transform (SIFT) matching performance decreases greatly when images are in different scales with complicated content and wide-baseline. In this paper, we address this problem, and propose a simple method to improve SIFT matching. The proposed method restricts the matching searching area into much smaller and more likely region to improve matching performance. Experiments shows that the proposed method has saved up to 90% matching time and increased up to 4% in the accuracy, compared with SIFT and previously solutions which only improve the matching accuracy.

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